The economic and social benefits associated with Further Education and Skills: Learning for those not in employment

London Economics and Ipsos MORI

AUGUST 2013 About London Economics

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t: +44 (0)20 7347 3000 f: +44 (0)20 7347 3800 Contents

Executive summary ........................................................................................................................ 5 Reasons for choice of learning and provider.............................................................................. 5 Reasons for choice of provider ..................................................................................................... 5 How learners found out about the course and referral routes...................................................... 6 Prior assessment .......................................................................................................................... 6 Waiting times................................................................................................................................. 6 The role and effectiveness of information, advice and guidance .................................................. 6 Reasons for non completion/ factors that would have assisted completion................................. 7 Course perceptions ....................................................................................................................... 7 Economic benefits associated with learning ................................................................................. 8 Perceived additionality – would they have achieved the benefits anyway? ................................. 9 The impact of learning on potential progression and further skills acquisition ............................ 9 Wider benefits associated with learning...................................................................................... 10 Satisfaction and well-being ......................................................................................................... 10

Introduction and Terms of reference .......................................................................................... 12 Comparison of the Individual Learner Record and sample information ..................................... 13 Presentation of descriptive statistics relating to population and sample of learners .................... 13 Additional information about sample ............................................................................................ 14 Qualification take up and learners’ prior attainment .................................................................... 15

Results and findings..................................................................................................................... 18 Economic characteristics of learners .......................................................................................... 18 Reasons for choice of training and prior expectations ................................................................. 20 Main reason for choosing provider ............................................................................................ 23 How learners found out about the course and referral ................................................................. 28 Prior assessment .......................................................................................................................... 29 The effectiveness of information, advice and guidance ................................................................. 33 Reasons for non completion/ factors that would have assisted completion .......................... 36 Course perceptions ............................................................................................................. 38 Course ease ..................................................................................................................... 39 Economic benefits associated with learning ................................................................. 40 Employment, job satisfaction and further learning ....................................................... 40 Current economic status ............................................................................................... 47 Perceived additionality – would employment outcomes have been achieved anyway? .... 50 The impact of learning on potential progression and further skills acquisition ............ 53 Wider social benefits associated with learning ............................................................. 55 Satisfaction and wellbeing ............................................................................................. 57 Annex 1 Methodological approach .................................................................................. 60 Survey population and sample frame ............................................................................ 60 Sample size and design ................................................................................................. 60 Questionnaire development and piloting ....................................................................... 60 Response rates ............................................................................................................... 61 Weighting ....................................................................................................................... 62 Annex 2 Additional information on sample .................................................................... 63 Assessment of match and reliability of sample ............................................................. 63 Executive summary

Ipsos MORI and London Economics were commissioned by the Department for Business, Innovation and Skills to undertake a detailed analysis of the benefits associated with Further Education and Skills for learners not in employment. The findings in this report are based on a telephone survey of 1,955 learners not in employment who received or completed their learning in 2011/12. In addition to focusing on the wider benefits associated with learning and qualification attainment, the research also explores learners’ reasons for undertaking the course; the role and effectiveness of information, advice and guidance (IAG); reasons for non-completion; and what might have happened in the absence of publicly funded training. This piece of analysis follows an earlier analysis of a wider population of 4,000 FE learners¹, and many of the results, especially in relation to the economic and social outcomes associated with education, training and skills acquisition are comparable between the studies.

Reasons for choice of learning and provider

Two in five learners (39%) undertook the course to improve their job prospects or raise their income, while a similar proportion (41%) wanted to gain new skills (including 11% who chose the course because it was a stepping stone to further learning). A minority were primarily motivated by wider benefits such as ‘meeting new people’ or ‘building self-confidence’ (cited by 3% each). These patterns mirror the findings observed among FE learners more generally.

Learners undertaking Level 1 and Level 2 qualifications were significantly more likely than those doing Entry Level courses to cite job-related prospects as the primary reason for their decision to undertake learning. Among the latter group, there was greater emphasis on gaining new skills and progression onto further or higher qualifications.

Learners’ motivations were also closely linked to their life-stage. For example, learners aged 25-39 were most likely to cite job-related factors, whilst younger learners (aged 19-24) were most likely to be doing the learning in order to progress to further learning at a higher level. Learners aged 40 plus were most motivated by skills acquisition per se.

Reasons for choice of provider

The main reason for learners’ choice of provider was the convenience of location (cited by 43%). Small minorities of respondents chose the provider because they offered a specific course of interest (8%), offered courses at convenient times (7%), offered good facilities (7%) or had a good reputation (3%). Personal recommendations was also a factor, with 14% choosing the provider as a result of a recommendation from either a Jobcentre Plus or a National Careers Service advisor, while 3% of respondents each mentioned the recommendations of a careers advisor at school or recommendations from parents/family or friends.

As would be expected, learners with caring responsibilities were more likely than average to cite convenient location and times as the main reasons for their choice of provider.

¹ “The impact of Further Education Learning”, BIS Research Report 104, January 2013 (here) Just 3% of learners indicated that they had no choice in the matter because the course was mandatory (Jobcentre Plus or the National Careers Service chose the provider).

**How learners found out about the course and referral routes**

Half of learners (51%) found out about the course themselves (i.e. self-referred). Almost a quarter of learners (22%) were told about it by a Jobcentre Plus adviser and a similar proportion (24%) found out through another organisation or individual. Just 3% reported finding out about the course through the National Careers Service (formerly Next Step(^2)). This figure may underestimate the role of the National Careers Service in encouraging individuals to undertake the learning and training, given that 24% of men and 19% of women who heard about the course from a Jobcentre Plus advisor were also referred to an interview with a National Careers Service advisor(^3).

Among learners who heard about the course through a Jobcentre Plus advisor, a quarter (or 7% of the overall sample) was told that they would risk losing their benefit if they failed to attend an interview with the National Careers Service advisor and/or the learning provider. Younger learners and learners attempting lower qualification levels were more likely to have been informed of the potential benefit sanction.

**Prior assessment**

Three in five learners (61%) indicated that someone had asked them about their prior qualification attainment before commencing the learning or training, and 66% reported that some assessment of their English, Maths or language skills had been undertaken. In only 57% of cases was there any discussion of how the training might help the learner get a job. Younger learners (aged 19-24) were more likely than learners aged 40 plus to recall having been asked about prior qualification attainment, being assessed for their English, Maths and languages skills or having a discussion on how the training will help them find work.

**Waiting times**

Over half of learners (53%) waited less than 2 weeks before starting the learning and an additional 26% waited between 2 and 4 weeks. Younger learners waited longer between being referred and starting their training (44% commenced within 2 weeks compared with 54% of learners aged 25-39 and 61% of learners aged 40 plus). There was a relatively rapid training start for learners attempting Level 1 qualifications - 63% commenced their training within 2 weeks of referral compared with 33% of learners undertaking a Level 3 and 28% of learners undertaking a Level 4.

**The role and effectiveness of information, advice and guidance**

The majority of learners felt well informed about their course (measured in terms of ‘net positives’). Specifically 80% felt well informed about the course content and the subjects that would be covered; 74% and 78% of men and women (respectively) felt well informed

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(^2) Next Step was replaced by the National Careers Service in April 2012, but would have advised many of the learners in this survey. The use of the term NCS covers both Next Step and NCS provision.

(^3) There is no information on whether the National Careers Service advisor provided advice on the training and prompted the referral about the amount and standard of the work required of them. Substantive information on whether to study the course ‘in one go’ or in units appeared less prevalent - 67% felt well informed on this. The areas of information advice and guidance where learners considered themselves to be the least well informed (in relative terms) related to the labour market potential of the learning – just 54% felt well informed on the potential of the course to get them a good job/career and 64% feeling well informed on how the training would help them gain skills to use in a job. These results are very similar those generated in the preceding analysis focusing on the wider population of FE learners.

There is a correlation between the degree to which individuals believed they were well informed and course completion. Learners who had completed their course or training were between 5 and 12 percentage points more likely to recall feeling well informed in relation to the content of the course; the amount of work required; how the course would help them gain job-related skills; and labour market potential.

**Reasons for non completion/ factors that would have assisted completion**

Among learners who failed to complete their course, half stated that the primary reasons were personal or circumstantial, such as family or health related issues (with a greater impact on women than on men). However, this may be somewhat deceptive, as in a quarter of these cases, respondents indicated that the main reason that they did not complete the learning aim was because they found work.

In 18% of cases, the primary reason was course-related (15% for women and 22% for men). Time pressures and workload issues impacted course completion for 20% of men and 19% of women while in only 6% of cases did respondents cite financial concerns as the primary reason for non-completion.

**Course perceptions**

Completers were exceptionally positive about their learning experience: 93% of women and 88% of men were satisfied with their course; only 5% of women and 9% of men were dissatisfied. In aggregate, the results presented here are approximately 3 percentage points more positive compared to the course perception estimates generated in the wider analysis of FE learners.

Younger learners (aged 19-24) were marginally less satisfied with their course although still exceptionally positive. Specifically, 84% of younger learners were ‘fairly satisfied’ or ‘very satisfied’ compared with 93% and 91% (respectively) of learners aged 25-39 and 40 plus.

Learners undertaking Entry level, Level 1 or Level 2 qualifications were more likely to be satisfied with their course compared with those undertaking Level 4 qualifications (94%, 88% and 92% respectively compared with 81% at Level 4).

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4 The association between the two variables does not imply causation, as it could be the case that those learners failing to complete may have assessed the information, advice and guidance as being not particularly worthwhile as a result of failure to complete. Economic benefits associated with learning

The survey asked respondents to provide some information on the economic benefits that might have been associated with course completion. Completers (only) were asked to indicate their employment status following the conclusion of their learning aim.

There were large and significant economic benefits associated with undertaking and completing learning and training: 15% of men and 13% of women were in full-time paid employment after completion, while 11% of men and 20% of women were in part-time work. A further 4% of men and 2% of women were self-employed. Combining these estimates implies that 30% of men and 35% of women were in employment following the completion of their course. A further 7% of men and 13% of women were in voluntary or unpaid employment.

The information collected also indicates that the position gained was more often than not permanent in nature (58% of cases compared to 39% of employment opportunities that were temporary). In addition, there was some degree of employment persistence - 71% of men and 84% of women were still in the same employment position. However, of the 20% of respondents indicating that the job had actually come to an end, 50% indicated that their job duration was less than 3 months with a further 32% indicating the job duration was between 3 and 6 months.

There were some slight distinctions in the employment outcomes of learners by age. Although 29% of younger completers were in employment immediately post completion, the balance between full-time and part-time work was more uneven. Specifically, only 9% of completers aged 19-24 were in full-time employment (compared with 14% of completers overall), with 20% in part-time employment (compared with 16% of completers overall). The fragility of the employment outcome achieved by younger workers post-completion is also reflected in the proportion of younger respondents indicating that the job was temporary in nature (55%), the proportion stating that the job had ended (31%) or mentioning that the position had lasted for less than 6 months (95%). This compares to estimates of approximately 35%, 18% and 80% respectively for workers aged 25 plus.

The employment opportunities were associated with relatively low levels of earnings, although this is unsurprising given that pre-employment training (through Jobcentre Plus) is primarily aimed at entry level positions. For men, the annual earnings in the job immediately following completion were less than £10,000 per annum in 45% of cases and between £10,000 and £15,000 in a further 25% of cases, while more than 76% of women achieved annual earnings of less than £15,000 per annum (60% below £10,000 and 16% between £10,000 and £15,000). Earnings in excess of £25,000 were achieved by less than 1%.

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5 Although not directly comparable, the main survey of FE learners indicated that following the receipt of education and training, 35% of men and 29% of women indicated that they had got a better job, while 18% of men and 12% of women indicated that they had received a promotion.

6 Note that of those individuals that stated they were engaged in voluntary work or unpaid work prior to the learning aim, the analysis suggests that approximately 31% were still undertaking voluntary or unpaid work. 20% indicated they were working as an employee; 38% were unemployed; 5% were looking after their home or family, while 4% indicated they were not working either because of temporary or long term illness or disability.

7 Information from the LFS indicates that 94% of employees are in permanent positions while 6% in temporary positions (LFS 2012 Q1).

8 In the wider economy, approximately 7.0% of employees have been with their current employer for less than 6 months, with a further 6.4% employed for with their current employer for between 6 months and 1 year (LFS 2012 Q1). However, against these positive outcomes, half of completers were not in employment following the completion of their course or training (57% of men and 45% of women). When asked about the reasons for not being in employment, the responses highlight the extent to which learners are either ‘close’ or ‘distant’ from the active labour market. In particular, of those not actively seeking employment, 21% were waiting for the completion of the course or on the results of a job application. However, 22% were not seeking employment because of childcare of family responsibilities, with a further 33% of these learners citing health reasons for the decision not to actively seek work (42% of men compared to 27% of women). One in seven learners (14%) indicated that they were either retired, in training or faced language barriers. In only 1% of cases do respondents mention that the lack of qualifications or experience affected their job-search activities.

**Perceived additionality – would they have achieved the benefits anyway?**

Completers who were in employment were asked to consider the extent to which the training undertaken had contributed to them finding work. Although the sample sizes are particularly small(^9), the analysis suggests that 44% of completers in employment thought they would have found work anyway. An additional 35% of completers in-work indicated they would have found work though not as quickly, while 21% believed they would either ‘probably’ or ‘definitely’ not found employment in the absence of the training. Men were more likely to state that they would have found work anyway in the absence of training (89% compared with 72% of women).

**The impact of learning on potential progression and further skills acquisition**

In addition to the direct economic effect associated with training in the form of enhanced employment and earnings outcomes, the analysis strongly suggests that undertaking training has a strong positive effect on learners’ views in relation to further learning and training. For example, 84% of learners had become more enthusiastic about learning (81% of men and 86% of women), and this compares favourably to the 80% of completers in the main FE learner survey indicating that they had become more positive about learning.

There was also an impact on whether further training and learning might take place, with 86% of women and 83% of men indicating that they were more likely to undertake further learning, as well as an increase in the likelihood that further training would be undertaken at a higher level (80% of women and 78% of men). The findings support the widely held belief that training leads to further training and acts as a stepping stone to higher and more economically productive skills acquisition.

Younger learners (aged 19-24) were 5 percentage points more likely to undertake further learning and training compared with learners aged 40 plus, and 15 percentage points more likely to undertake further learning at a higher level. Learners aged 25-39 were the most enthusiastic about learning (86%), the most likely to undertake further learning and training (89%) and the most likely to undertake further learning at a higher level (84%). These outcomes may reflect the fact that these learners were better informed about the impact of

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(^9) Only 295 individuals responded to the question, which is 15% of the total sample. their learning on their career prospects and the associated economic value associated with skills acquisition.

As would be expected, there were significant differences in perceived outcomes among learners depending on completion status. Completers were 11 percentage points more likely to be more enthusiastic about learning (86% compared with 75% of non-completers); 9 percentage points more likely to consider undertaking further education and training (86% compared with 77% of non-completers); and 20 percentage points more likely to undertake additional learning at a higher level (84% compared with 64% of non-completers). These differences between the views of completers and non-completers are again comparable with the results of the previous survey of FE learners.

**Wider benefits associated with learning**

Learners were also asked for their views on the wider benefits of learning. Four in five (81%) said they had gained self-confidence or self-esteem following the training episode and 72% had made new friends or taken part in voluntary work. Three quarters (76%) said that it had helped them make better use of their spare time and 30% mentioned that the course had enabled them to assist their children with school work. There were some gender differences (especially in relation to the ability to assist children with school work) although in general these are relatively small. Only 5% of learners indicated that the course had had none of the wider economic benefits presented.

Three quarters of learners (75%) indicated that they now had a better idea of what to do with their lives, and 66% stated that their quality of life had improved as a result of undertaking the education and training activity. Training appeared to provide some degree of additional direction to younger learners (aged 19-24) with 83% stating that this was the case, while 73% of younger learners indicated that the learning had improved their quality of life.

As would be expected, differences by completion status persist with completers significantly more likely than non-completers to report wider benefits. For example, completers are 10 percentage points more likely to report gaining self-confidence or self-esteem; 24 percentage points more likely to undertake social or voluntary work; 7 percentage points more likely to indicate that the training has assisted them in helping their children with their studies; 8 percentage points more likely to respond that they now make better use of their spare time; and 6 percentage points less likely to indicate that the training had impacted none of the above. In addition, 78% of completers also mentioned that their quality of life had improved compared to 53% of non-completers.

Again, these results are very similar to those generated as part of the analysis of the wider sample of FE learners, both at an aggregate and disaggregated level.

**Satisfaction and well-being**

In a final element of analysis, information was collected on learners’ general well being. The analysis suggests that there are differences between men and women in response to the question “overall, how satisfied are you with life nowadays?” with women generally being more positive about their circumstances compared to men (a score of 7.26 compared with 6.52 for men), although these general wellbeing measures do lag behind comparable estimates for the population as a whole (7.40\\textsuperscript{10}). The equivalent estimates generated as part of the previous analysis of FE learners stood at 7.57 and 7.40 respectively. In response to the question “overall, to what extent do you feel the things you do in your life area worthwhile?”, women also indicated that they were more content, posting an average score of 7.71 compared with 7.05 for men.

We also considered whether a person's employment status had an impact on general wellbeing measures. We found that learners in employment post-completion of their learning aim were more likely to give high scores compared with those not in employment (8.63 compared with 7.49 among those who were not in employment), which in part explains the differences in the satisfaction measures between the more general population of FE learners and the current analysis of learners not in employment.

\\textsuperscript{10} ONS (2011). The mean measure of subjective well being using the same question as adopted in this survey stood at 7.40. See http://www.ons.gov.uk/ons/rel/mro/news-release/initial-investigation-of-subjective-well-being---ons-opinions-survey/initial-investigation-of-subjective-well-being---ons-opinions-survey-nr.html for more information (accessed 25 July 2012) Introduction and Terms of reference

Ipsos MORI and London Economics were commissioned by the Department for Business, Innovation and Skills undertake a detailed exploration of the economic, education and training related and wider benefits associated with Further Education and Skills for learners not in employment.

Ipsos MORI undertook a telephone survey of a representative sample of 1,955 learners from the Individual Learner Record between February – March 2012 (Annex 1 contains full details on the methodology). The analysis in this report assesses the economic outcomes associated with learning and skills acquisition (such as employment and earnings), as well as education and training related outcomes (such as respondents’ appetite for learning and training progression). We also address the wider benefits associated with learning including general well-being levels, but also the extent to which undertaking training and learning impacted on learners’ social well-being (such as improved self-confidence, self-esteem etc). The analysis is presented at both an aggregated and disaggregated level. The report is set out as follows:

In the section “Comparison of the Individual Learner Record and sample information” we present some summary descriptive statistics relating to the composition of the achieved sample and the extent to which the personal and socioeconomic characteristics of this sample match those of the population of learners from the ILR.

In the “Results and findings” section, we provide further information on the economic characteristics of the sample of learners, and in the subsequent sub-sections, provide an analysis of the primary reasons for undertaking training in the first instance and the choice of provider, the role and effectiveness of information, advice and guidance and referral routes. We then provide a more detailed examination of the outcomes associated with learning. First, we consider the extent to which learners completed their learning aim, and the dominant reasons why learners may have failed to complete their course of learning. We also address the perceptions that learners had towards the learning that they undertook in terms of their satisfaction with the course undertaken and the difficulty of the course. In the final sub-sections of the chapter, we assess the core-economic, training and learning related outcomes, as well as the wider social outcomes associated with further education and learning. Comparison of the Individual Learner Record and sample information

Presentation of descriptive statistics relating to population and sample of learners

In Table 1, we present information on some of the basic socioeconomic characteristics of the weighted sample alongside information on the characteristics of the learner body from which the sample was taken. The descriptive statistics indicate that there is strong comparability over many of the variables that were used to sample the learner data, including gender, level of qualification and age of attainment.

| Table 1: Comparison of information from ILR (2011/12) and weighted sample | |-----------------------------|-----------------------------|-----------------------------| | | Population | Sample | | Gender | | | | Male | 19,930 | 874 | | Female | 24,631 | 1081 | | Age | | | | 19-24 | 13,170 | 579 | | 25-39 | 16,922 | 742 | | 40+ | 14,469 | 634 | | Qualification Aim | | | | Entry level | 4,246 | 188 | | Level 1 | 8,948 | 393 | | Level 2 | 23,805 | 1042 | | Level 3 | 7,098 | 313 | | Level 4 | 464 | 20 | | Ethnic Origin | | | | White – British | 27,846 | 1,280 | | White – other | 3,142 | 89 | | Bangladeshi | 547 | 26 | | Indian | 1,169 | 59 | | Pakistani | 1,785 | 82 | | Asian other | 1,290 | 43 | | Black African | 3,310 | 148 | | Black Caribbean | 1,477 | 33 | | Black other | 703 | 33 | | Chinese | 188 | 10 | | Mixed | 1,403 | 62 | | Any other | 1258 | 59 | | Not known/ provided | 443 | 1 | | Attainment | | | | Completed - fully achieved | 12,310 | 865 | | Continuing | 21,880 | 810 | | Failed/withdrawn | 9,366 | 281 |

Source: Ipsos MORI and London Economics (2012). Note: Base sample – 1,955.

The analysis from Table 1 indicates that although there is a close match on a number of the variables, there are some small differences between the sample and the initial source. of learner information. In particular, the sample contains a slightly higher proportion of individuals that indicate they are white-British (65% compared to 62% from the 2011/12 ILR), but also a slightly higher proportion indicating that they are Indian (3.0% compared to 2.6% from the 2011/12 ILR) and a slightly lower proportion of respondents that indicate they are White-other (4% compared to 7% from the 2011/12 ILR). It should be noted that some of these last differences in the sample are driven by the fact that only a very low proportion of the sample refused or did not provide information relating to ethnic origin.

One area where there was some difference in the characteristics of learners related to the extent of learning aim completion. Specifically, although the sample drawn from the 2011/12 ILR indicated that 28% of learners fully achieved their learning aim, the corresponding proportion in the achieved sample of respondents stood at 44%. In contrast, the proportion of learners drawn from the ILR that were classified as having failed or withdrawn from their learning aim stood at 21% compared to 14% in the achieved sample. The differences in attainment outcomes between the sample of respondents and the sample drawn from the ILR may result in providing a more optimistic view of the aggregate impact of qualification attainment as a whole.

Additional information about sample

In terms of the other data collected as part of the survey, Table 2 provides some additional information on the personal and socioeconomic characteristics of learners.

| Table 2: Personal characteristics of learner sample | |-----------------------------------------------| | Male | Female | Total | |------|--------|-------| | **Age** | | | | 19-24 | 351 | 40.1% | 229 | 21.1% | 579 | 29.6% | | 25-39 | 276 | 31.6% | 466 | 43.1% | 742 | 37.9% | | 40+ | 248 | 28.3% | 387 | 35.8% | 634 | 32.4% | | **Marital Status** | | | | Single | 614 | 70.3% | 503 | 46.5% | 1,117 | 57.1% | | Married | 166 | 19.0% | 360 | 33.3% | 527 | 26.9% | | Civil partner | 32 | 3.7% | 30 | 2.8% | 62 | 3.2% | | Separated/Divorced/ Widowed | 61 | 7.0% | 188 | 17.4% | 249 | 12.8% | | **Children** | | | | Yes | 218 | 25.0% | 578 | 53.5% | 796 | 40.7% | | No | 655 | 75.0% | 508 | 46.5% | 1,157 | 59.3% | | **If 'yes', number of children** | | | | One | 79 | 36.1% | 186 | 32.2% | 265 | 33.3% | | Two | 76 | 35.0% | 236 | 40.8% | 312 | 39.2% | | Three | 47 | 21.6% | 113 | 19.5% | 160 | 20.1% | | Four | 11 | 5.1% | 34 | 5.8% | 45 | 5.6% | | Five or more | 5 | 2.2% | 9 | 1.6% | 14 | 1.8% | | **If 'yes', age of youngest child** | | | | up to 5 years | 96 | 35.9% | 186 | 35.4% | 282 | 41.9% | | 6-10 years | 56 | 20.8% | 220 | 42.0% | 275 | 40.9% | | 11-15 years | 93 | 34.5% | 60 | 11.5% | 34 | 5.0% | | 16-18 years | 24 | 8.9% | 57 | 10.8% | 81 | 12.0% | | refused | 0 | 0.0% | 2 | 0.3% | 2 | 0.3% | | **Health problems** | | | | Yes | 208 | 23.9% | 184 | 17.0% | 392 | 20.1% | | No | 664 | 76.1% | 897 | 83.0% | 1,561 | 79.9% |

Source: Ipsos MORI and London Economics (2012). Note: Base sample =1,955. The information indicates that although the sample is broadly reflective of the pool of learners contained within the ILR, there are some differences between men and women. In particular, the sample of learners appears to contain a larger proportion of male learners between the ages of 19 and 24 (40% of all male learners compared to 21% amongst female learners), while the largest category of female learners is in the 25-39 age group (43% compared to 32% of men). Possibly reflecting this difference in age structure, there are also differences in the marital status according to gender, with 70% of men being single and 23% being married or in a civil partnership (compared to 46% of women indicating they are single and 36% responding that they are either married or in a civil partnership). Similarly, women are significantly more likely to indicate that they have a dependent child (53% compared to 25%) although there is little difference across genders in the age of the youngest child.

**Qualification take up and learners’ prior attainment**

Between Table 3 and Table 5, we present information on the highest qualification held by respondents at the start of the course and the qualification type (both variables are self-reported by respondents). One point to note is that we collect no information on the length of the qualification, or any information on whether the learning aim was a stand-alone qualification or a unit contributing to a full qualification.

Around one eighth of the sample is in possession of a qualification at level 4 or above, with around 14% and 24% in possession of a qualification at Level 3 and Level 2 respectively. More than 33% of survey participants reported that they have either no formally recognised qualifications or were in possession of qualifications at Level 1. There was limited variation across gender, with one-third of men and women of men in possession of low or no qualifications.

| Qualification Level | Male | Female | Total | |---------------------|------|--------|-------| | No qualifications | 113 | 118 | 231 | | Below level 2 | 177 | 242 | 419 | | level 2 | 233 | 244 | 478 | | level 3 | 135 | 140 | 275 | | level 4 or above | 87 | 154 | 241 | | Other | 79 | 127 | 205 | | Don’t know | 51 | 56 | 107 |

Source: Ipsos MORI and London Economics (2012). Note: Base sample =1,955.

Turning to the disaggregated analysis of the qualifications undertaken, the majority of respondents (34%) identified the qualification aim undertaken as an Award, Certificate or Diploma, followed by National Vocational Qualifications, City & Guilds and BTECs (around 14%, 11% and 10% respectively). Again, there is some variation by gender, with women less likely than men to undertake a BTEC (7% vs. 14%) or a City & Guilds qualification (9% vs. 15%) and more likely to undertake a qualification defined as Award, Certificate or Diploma (36% vs. 31%).

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11 Note that using information from the Labour Force Survey (2012 Q1), the proportion of unemployed individuals in possession of no qualifications stands at 23.4%, while a further 14.8% are in possession of qualifications below Level 2. Approximately 21% of learners have Level 2 qualifications or a trade apprenticeship (compared to 24% in Table 3, while 13% have Level 3 qualification (compared to 14% in Table 3). Therefore, although the aggregate proportion in possession of either low or no qualifications is broadly equivalent, the sample of learners responding to this survey is marginally more qualified. Further details on level of prior achievement and qualification type are presented in Table 5, where we provide a cross-tab of the two variables. Looking at the distribution of qualification type by prior achievement, we can see that almost half of the respondents with no prior qualifications reported to have undertaken an Award, Certificate or Diploma (42%), compared to only 30% of respondents with prior achievement at Level 1 or Entry level. The next most popular qualification across all prior ability levels are National Vocational Qualifications which are undertaken by between 12% and 15% of learners (although with a slight dip in the proportion of learners with prior attainment at Level 2 and Level 3). The next most common vocational qualifications undertaken are City & Guilds and BTEC qualifications, where 15% of learners undertaking City & Guilds qualifications have either low or no formally recognised qualifications (compared to 3% of learners undertaking BTEC qualifications).

As a note of caution, it should be remembered that some categories, such as Awards, Certificates or Diplomas may cover a variety of different courses and also some respondents may be unable to identify a specific aim title and therefore indicate a general term (such as award etc.) For instance “Awards, Certificates and Diplomas” are offered by a number of different awarding bodies, including many of those listed previously, so it is impossible to say, for example, that there were 207 learners on a City & Guilds course (final column, fifth row), as there may have been more learners undertaking City & Guilds qualifications identified within the Awards, Certificates and Diplomas category.

### Table 5: Level of prior achievement and qualifications undertaken

| Qualification | No Quals. | Below level 2 | Level 2 | Level 3 | Level 4 or above | Other/ don’t know | Total | |-------------------------------|-----------|---------------|---------|---------|------------------|-------------------|-------| | Advanced award/Cert./Dip. | 0.7% | 2.7% | 3.4% | 6.5% | 3.0% | 4.1% | 64 | | Award/Certificate/Diploma | 42.0% | 29.7% | 32.9% | 29.3% | 42.2% | 34.5% | 623 | | GCSE | 10.5% | 13.6% | 9.2% | 10.4% | 4.4% | 9.5% | 181 | | BTEC | 2.8% | 8.5% | 16.6% | 11.6% | 3.0% | 8.4% | 176 | | City & Guilds | 14.7% | 14.3% | 9.3% | 12.5% | 8.8% | 9.3% | 207 | | RSA | 0.0% | 0.0% | 0.0% | 0.0% | 0.4% | 0.2% | 2 | | GNVQ | 2.3% | 0.2% | 0.2% | 0.2% | 0.7% | 0.2% | 9 | | NVQ | 12.9% | 15.7% | 13.4% | 12.4% | 15.1% | 11.9% | 249 | | GCE A level | 1.5% | 1.4% | 3.5% | 1.1% | 1.3% | 3.7% | 41 | | AS level | 0.0% | 0.0% | 0.1% | 0.7% | 0.0% | 0.3% | 3 | | Key Skills | 1.7% | 3.2% | 3.1% | 4.6% | 3.3% | 1.7% | 54 | | ECDL | 1.2% | 2.9% | 1.7% | 2.2% | 7.9% | 2.3% | 52 | | ITQ | 0.0% | 0.2% | 0.4% | 0.4% | 1.3% | 0.4% | 8 | | OCR | 0.3% | 1.1% | 0.2% | 1.6% | 0.3% | 0.0% | 10 | | BCS | 0.0% | 0.3% | 0.3% | 0.0% | 0.5% | 0.9% | 7 | | Other | 3.9% | 2.5% | 2.0% | 4.4% | 5.3% | 6.5% | 69 | | Don’t know/ No answer | 4.6% | 3.7% | 3.7% | 2.0% | 2.0% | 6.1% | 69 |

Source: Ipsos MORI and London Economics (2012). Note: Base sample – 1,822. Results and findings

Economic characteristics of learners

In terms of the economic characteristics of learners, the analysis presented in Table 6 indicates that only 1.5% of learners were in self-employed immediately prior to commencing the qualification, while 3% were undertaking voluntary work or unpaid work; however, this in essence reflects the initial decision to only sample those individuals contained in the ILR indicating that they were not in employment. Given this initial sample selection the largest grouping of learners consisted of those individuals that were unemployed and looking for work (56% of men and 48% of women).

Table 6: Economic characteristics of learners – total and by gender

| Employment status prior to course? | Male | Female | Total | |-----------------------------------|------|--------|-------| | Self-employed | 13 | 16 | 29 | | Undertaking voluntary or unpaid work | 40 | 22 | 62 | | Doing a course/training a college/training provider | 254 | 249 | 503 | | Unemployed and looking for work | 495 | 494 | 989 | | Looking after the family or home | 15 | 203 | 218 | | Sick or injured | 50 | 39 | 89 | | Retired | 7 | 8 | 16 | | Other | 14 | 5 | 19 |

| In receipt of benefits? | Male | Female | Total | |-------------------------|------|--------|-------| | Yes | 582 | 763 | 1345 | | No | 280 | 303 | 584 |

| If “yes”, which benefits | Male | Female | Total | |--------------------------|------|--------|-------| | Jobseekers’ Allowance | 407 | 308 | 715 | | Income support | 54 | 209 | 263 | | Incapacity benefit/ESA | 84 | 62 | 146 | | Housing benefit/council tax | 83 | 130 | 214 | | Child tax credit/working family tax credit | 58 | 323 | 381 | | Disability Living Allowance/carers allowance | 26 | 32 | 58 | | Child Benefit/EMA | 16 | 41 | 57 | | Pension | 1 | 9 | 10 | | Other | 21 | 24 | 45 |

| Working history | Male | Female | Total | |-----------------|------|--------|-------| | Never worked | 156 | 199 | 355 | | Spent most of my time not working | 129 | 167 | 296 | | Spent about as much time working as not working | 116 | 143 | 259 | | Worked solidly with one or two breaks | 305 | 408 | 713 | | Worked solidly without a break | 142 | 139 | 281 |

| Main barrier to employment | Male | Female | Total | |-----------------------------|------|--------|-------| | Lack of qualifications/skills/work experience | 253 | 305 | 558 | | No suitable jobs/vacancies | 214 | 180 | 394 | | Health, disability, age | 141 | 148 | 289 | | Lack of childcare /look after family members | 14 | 152 | 166 | | Language barrier/waiting for VISA | 16 | 35 | 51 | | Not looking for work/working PT | 19 | 29 | 48 | | Local transport/local jobcentre unhelpful | 20 | 9 | 29 | | Criminal record, motivations, pers. circumstances/ other | 37 | 53 | 90 | | No barriers/ don’t know/no answer | 268 | 327 | 595 |

Source: Ipsos MORI and London Economics (2012). Note: Base sample 1,955. Questions in relation to the nature of benefit receipt asked of only those respondents indicating that received benefits (n=1,345) In terms of other economic activity, 29% of men and 24% of women were undertaking a course or training at a college or training provider immediately prior to commencing the qualification, while a further 20% of women (and 2% of men) were engaged in home care and family responsibilities. Around 1 in 20 of the sample of respondents indicated that they were sick or disabled (6% of men and 4% of women).

Over two thirds of respondents (66% of men and 71% of women) were in receipt of benefits (69% of the overall sample), with the greatest proportion in receipt of Jobseeker’s Allowance. There are some large differences between men and women. Of those benefit claimants, 54% of men indicated they were in receipt of Jobseeker’s Allowance compared to 27% of women. However, a further 7% of male benefit claimants and 18% of female benefit claimants were in receipt of Income Support. The next largest incidence of benefit receipt related to Child Tax credit/Working Family Tax Credits (8% of male benefit claimants and 28% of female benefit claimants). Finally, one in ten learners was in receipt of either Incapacity Benefit or Disability Living Allowance.

In terms of working histories, half (51%) of learners had been in employment (either solidly or with one or two breaks), with little differentiation between the sexes. Just over one in ten (13%) of learners had spent an equal amount of time in employment and out of work, while the remaining 33% indicated that they have either never worked (18%) or spent most of their time not in work (15%).

The survey also asked learners about the extent to which there were barriers preventing them from entering employment. Three-in-ten respondents (30%) indicated that there were no barriers stopping them from returning to work. However, the greatest barrier to employment mentioned was the perceived lack of qualifications or work experience (accounting for 29% of learners). In relation to other barriers to employment, 20% of learners not in employment responded that there were no suitable jobs or vacancies, while a further 15% of respondents indicated that they had a health problem or disability. As with a number of other studies of this nature, the availability of high quality or affordable childcare was perceived as a significant barrier in the return-to-work decision for women with 14% citing this as the primary barrier. Reasons for choice of training and prior expectations

Table 7 provides information on the main reason why individuals undertook learning in the first instance. Two in five learners (39%) were motivated by economic or job related factors – that is to improve their job prospects, gain a new career or to augment their income. Men were marginally more likely to undertake additional learning and training for economic or job related reasons compared to women.

Table 7: Reasons for choice of training – by gender

| Main reason for undertaking course? | Male | Female | Total | |-----------------------------------|------|--------|-------| | Improve my job prospects/get a new job or new career | 340 38.9% | 401 37.1% | 742 37.9% | | To increase my income | 8 0.9% | 14 1.3% | 22 1.1% | | To learn something new/gain new skills | 252 28.8% | 334 30.8% | 586 30.0% | | Personal interest in the course | 1 0.1% | 2 0.1% | 3 0.1% | | To go on to further or higher learning | 108 12.3% | 105 9.7% | 213 10.9% | | To meet new people/build my self confidence | 23 2.6% | 43 3.9% | 65 3.3% | | Because it was at a time/place that suited me | 8 0.9% | 15 1.4% | 24 1.2% | | Because I did not have to pay for it | 8 0.9% | 5 0.5% | 13 0.6% | | National Careers Service or JCP adviser told me about it | 8 0.9% | 10 1.0% | 19 0.9% | | Mandatory | 2 0.2% | - | 2 0.1% | | Recommended by family/friends/employer/tutor | 2 0.2% | - | 2 0.1% | | To help/ support my (grand)children with homework | 0 0.0% | 1 0.1% | 1 0.1% | | Other | 82 12.8% | 128 13.8% | 210 13.3% | | Total | 842 100.0% | 1058 100.0% | 1,902 100.0% |

Source: Ipsos MORI and London Economics (2012). Note: Base sample 1,902

Two in five learners (41%) undertook training to further their skills and training including 30% who wanted to learn something new or to gain new skills, while 11% of respondents indicated that they undertook the additional learning in order to go on and undertake some form of further or higher learning (12% for men and 10% for women). The options relating to wider potential benefits were less important for learners, with less than 3% mentioning ‘meeting new people’ or ‘building self confidence’ as the primary reason for engaging in learning. Reasons relating to convenience, the limited financial contribution or the mandatory nature of the course, were considered most important by less than 1% of learners.

When the equivalent analysis was undertaken by age group (Table 8), qualification level (Table 9) and referral route (Table 11), there were some interesting differences in the rationale for undertaking the learning or training. Specifically, individuals aged 25-39 were the most likely to engage in training for economic reasons (with 45% of these learners indicating that they had undertaken the additional education and training to improve their job prospects or gain a new career compared to 33% of younger learners and 40% of older learners).

Rather than focusing on the explicit economic impact associated with qualification attainment, for younger learners, the education and training undertaken was more often perceived as a stepping stone to further learning at a higher level (26% of 19-24 year olds compared to between 7% and 3% for those aged 25-39 and 40 plus, respectively). However, there may be a gap emerging from the responses of younger learners in the sense that although they are more likely to state that they undertook the specific learning aim to go onto to further of higher learning, they were less likely (compared to older learners) to indicate that they have undertaken the learning aim with the specific objective of learning something new or gaining a new skill. In this sense, younger learners’ appear to be more focussed on the process of undertaking learning (and perceive education and training to be more of a ‘consumption’ good) while older learners are more focused on the ultimate outcomes associated with qualification attainment (skills acquisition) and in this sense perceive qualification attainment to be more of an ‘investment’ good.

Table 8: Reasons for choice of training – by age

| Reason for choice of training | 19-24 | 25-39 | 40+ | |------------------------------|-------|-------|-----| | Improve job prospects/get a new job or new career | 179 | 319 | 244 | | To increase my income | 6 | 11 | 4 | | To learn something new/gain new skills | 137 | 226 | 223 | | Personal interest in the course | 3 | 0 | 0 | | To go on to further or higher learning | 144 | 52 | 17 | | To meet new people/build my self confidence | 11 | 22 | 35 | | Because it was at a time/place that suited me | 3 | 8 | 13 | | Because I did not have to pay for it | 5 | 4 | 4 | | National Careers Service or JCP adviser told me about it | 2 | 6 | 11 | | Mandatory | 2 | 0 | 0 | | Recommended by family/friends/employer/tutor | 0 | 2 | 0 | | To help/ support my (grand)children with homework | 0 | 1 | 0 | | Other | 58 | 79 | 73 |

Source: Ipsos MORI and London Economics (2012). Note: Base sample 1,955.

There is also an increasing relationship between the relative importance of economic factors in determining whether additional learning is undertaken and qualification level. In particular, 27% of learners undertaking an Entry level qualification indicate the primary reason being economic related, compared to 38% of Level 1 learners and 44% of Level 2 learners (although the relationship is not strictly increasing beyond Level 2). Conversely, the need to learn something new, gain new skills and to go on to further or higher learning was considered to be the fundamental rationale for qualification attainment amongst those undertaking the lowest level learning aims. For those undertaking Entry level qualifications, the dominant reason for undertaking the learning aim related to the need or wish to learn something new or gain new skills (35%), while a further 15% indicated that they wanted to use the learning aim to progress onto further or higher qualification attainment (compared to 30% and 10% at Level 2 respectively).

Table 9: Reasons for choice of training – by level

| Reason for choice of training | Entry | 1 | 2 | 3 | 4 | |------------------------------|-------|---|---|---|---| | Improve job prospects/get a new job or new career | 26.0% | 37.7% | 42.7% | 37.3% | 24.5% | | To increase my income | 1.2% | 0.6% | 1.1% | 1.7% | 5.1% | | To learn something new/gain new skills | 34.5% | 33.6% | 30.5% | 25.9% | 31.6% | | Personal interest in the course | 0.6% | 0.0% | 0.0% | 0.5% | 0.0% | | To go on to further or higher learning | 14.9% | 7.2% | 9.6% | 19.4% | 8.7% | | To meet new people/build my self confidence | 8.2% | 5.3% | 2.8% | 0.5% | 14.3% | | Because it was at a time/place that suited me | 2.0% | 1.6% | 1.2% | 0.7% | 0.0% | | Because I did not have to pay for it | 0.0% | 1.0% | 0.8% | 0.3% | 0.0% | | National Careers Service or JCP adviser told me about it | 0.6% | 2.2% | 0.9% | 0.0% | 0.0% | | Mandatory | 0.0% | 0.5% | 0.0% | 0.0% | 0.0% | | Recommended by family/friends/employer/tutor | 0.0% | 0.4% | 0.0% | 0.0% | 0.0% | | To help/ support my (grand)children with homework | 0.0% | 0.3% | 0.0% | 0.0% | 0.0% | | Other | 11.8% | 9.5% | 10.5% | 13.7% | 15.8% | | Total | 182 | 375 | 1015 | 308 | 20 |

Source: Ipsos MORI and London Economics (2012). Note: Base sample 1,955. We also attempted to understand the extent to which the reasons for choice of training depended on the respondent’s economic status prior to commencing the programme of study. Looking at the categories with the most respondents (those who are unemployed and looking for work or in education and training), the analysis in Table 10 suggests that 44% of unemployed learners undertook the learning aim with the intention of improving their employment prospects (compared to 30% of respondents in education and training prior to commencing the learning aim in question), while approximately 32% of unemployed learners suggested that learning something new or gaining new skills was the main reason (compared to 21% of those in education and training). Only 6% of unemployed learners indicated that the primary reason related to going on to further or higher learning, which is substantially less than the 25% of respondents who are already in education and training. This information is presented in Table 10 below.

Table 10: Reasons for choice of training – by selected pre employment status

| Reason for Undertaking Course | Self-employed | Education / training | Voluntary Work | Unemployed | |-------------------------------|---------------|----------------------|----------------|------------| | Improve job prospects/get a new job or new career | 18.7% | 29.8% | 44.2% | 43.7% | | To increase my income | 3.5% | 2.1% | 0.0% | 0.9% | | To learn something new/gain new skills | 46.0% | 21.5% | 28.5% | 31.7% | | Personal interest in the course | 0.0% | 0.4% | 0.0% | 0.1% | | To go on to further or higher learning | 5.9% | 24.7% | 2.6% | 5.8% | | To meet new people/build my self confidence | 5.2% | 2.8% | 3.2% | 3.1% | | Because it was at a time/place that suited me | 1.7% | 1.2% | 3.9% | 0.8% | | Because I did not have to pay for it | 0.0% | 0.7% | 0.0% | 0.5% | | National Careers Service or JCP adviser told me about it | 0.0% | 0.4% | 0.0% | 1.5% | | Mandatory | 0.0% | 0.2% | 0.0% | 0.1% | | recommended by family/friends/employer/tutor | 0.0% | 0.0% | 0.0% | 0.0% | | To help/support my (grand)children with homework | 0.0% | 0.0% | 0.0% | 0.1% | | Other | 19.0% | 16.3% | 17.6% | 11.6% | | Total | 29 | 496 | 93 | 989 |

Source: Ipsos MORI and London Economics (2012). Note: Base sample 1,955.

Presented in Table 11, the variation in the reasons for undertaking additional education or training also depends on the referral route: 40% of individuals who self-refer indicate that they undertake the training for economic reasons, with an equivalent proportion (41%) mentioning that they wish to go onto to further or higher education, learn something new or gain a new qualification. For those individuals that were referred through a National Careers Service advisor, 58% mention that the primary reason for undertaking the learning aim was in order to go on to further or higher education (14%) or to learn something new or gain a new qualification (44%). For those individuals referred through a Jobcentre Plus advisor, 45% mentioned that the primary reasons related to their desire to improve their job prospects or gain a new job or career, compared to 31% of respondents who wished to learn something new or gain new skills.

Table 11: Reasons for choice of training – referral route

| Main reason for undertaking course? | Self-referred | JCP Adviser | National Careers Service | Other | |------------------------------------|---------------|-------------|--------------------------|-------| | Total | 29 | 496 | 93 | 989 | Main reason for choosing provider

We also assessed what factors determined the choice of the training provider. Table 12 presents the information at a disaggregated level allowing for the explicit consideration of all the reasons provided by learners. Note that respondents were able to provide more than one answer to the question, so the column totals exceed the total number of respondents. As can be seen, across the entire sample of learners, the dominant factor for the decision to select a particular provider was that the FE College or training provider offered a convenient location or courses at convenient times (43% and 7% of the total number of responses respectively, with few differences depending on gender), while the provider offering the specific course of interest to the learner was cited by almost 8% of learners. Other factors specifically related to the provider that were commonly cited included the provider’s reputation in terms of pass rates and more general course reputation (3% combined) and the course/training provider’s facilities (7%).

The analysis demonstrates the key range and role of recommendations in determining the choice of provider. The information in Table 12 suggests that 14% of learners chose the provider as a result of a recommendation from either a Jobcentre Plus or a National Careers Service advisor, while 3% of respondents each mentioned the recommendations of a careers advisor at school or the recommendations of parents/family members or friends.

The other reasons provided for the choice of provider were less common. In 3% of cases, respondents indicated that they had no choice in the matter because the course was mandatory (with a Jobcentre Plus advisor or National Careers Service advisor choosing the provider); because the provider was the only provider to accept the applicant (in 2% of cases), or because there were no other providers in the area. In just over 2% of cases was the primary reason was associated with the sight of advertising or leafleting promoting the College or an open day/careers fair at the College/training provider. Very few individuals explicitly stated that they selected the provider solely because they believed that it would assist them seeking employment or find a job.

In terms of potential cost drivers determining the choice of provider, only 3% of learners indicated that their selection of provider was as result of the costs being lower than an alternative provider, while a further 2% mentioned that the course was free at that particular provider. The economic and social benefits associated with Further Education and Skills: Learning for the unemployed

Table 12: Reasons for choice of provider – by gender

| Reason | Male | Female | Total | |---------------------------------------------|--------|---------|--------| | Convenient location/nearest | 389 | 458 | 847 | | Offered course I wanted | 141 | 161 | 302 | | Has best reputation (general) | 53 | 98 | 151 | | Has best reputation for pass rates | 4 | 8 | 12 | | Has best reputation for my course | 29 | 18 | 47 | | Did a course there previously | 48 | 64 | 112 | | Friends were going there/friend recommended | 46 | 76 | 122 | | Recommended by career advisor/school | 21 | 29 | 50 | | Recommended by National Careers Service/JCP| 115 | 156 | 271 | | Recommended by parents/other family member | 21 | 34 | 55 | | Offered a course at convenient times for me | 32 | 106 | 138 | | Had no choice – JCP/National Careers Service chose | 10 | 5 | 15 | | Had no choice – only one that accepted me | 4 | 4 | 8 | | Had no choice – no other providers in this area | 16 | 18 | 34 | | Lower cost compared to other providers | 23 | 30 | 53 | | Could study from home/on the internet/self study | 5 | 36 | 41 | | Good facilities/environment/staff | 19 | 25 | 44 | | Helps secure employment/find a job | 3 | 9 | 12 | | Free | 12 | 18 | 30 | | Needed something to do/occupy myself | 2 | 1 | 3 | | Offered good opportunities/future prospects | 5 | 2 | 7 | | Saw advertising/leaflet/open day | 18 | 25 | 43 | | Wanted to gain more knowledge/qualifications| 12 | 11 | 23 | | Wanted to move away/try a new college | 4 | 1 | 5 | | Other specified recommendation | 18 | 16 | 34 | | Other | 25 | 22 | 47 | | Don’t know | 8 | 12 | 20 | | No answer | 8 | 6 | 14 | | Don’t know | 8 | 6 | 14 |

Source: Ipsos MORI and London Economics (2012). Note: Base sample 1,955

The analysis also suggests that ‘provider-related’ factors were more likely to be considered the primary determinant for the decision to undertake a particular course amongst younger learners (for instance, 48% for 19-24 year olds mentioned the convenient location compared to 38% for learners aged 40 plus, while 11% of younger learners mentioned the providers reputation compared to 6% of older learners). However, prior experience of the learning provider also plays an important role, with 11% of younger learners mentioning the fact that they had undertaken a course there previously as being a significant reason for choosing the provider again (compared to 5% of older learners).

Table 13: Reasons for choice of provider – by age

| Reason | 19-24 | 25-39 | 40+ | |---------------------------------------------|-------|-------|------| | Convenient location/nearest | 278 | 330 | 239 | | Offered course I wanted | 93 | 110 | 100 | | Has best reputation (general) | 62 | 55 | 35 |

Source: Ipsos MORI and London Economics (2012). Note: Base sample 1,955 There were significant differences in the rationale for selecting a particular provider depending on referral route. Self-referred learners were more likely to mention issues relating to the location or convenience of the learning provider (52% compared to 30% of those referred through Jobcentre Plus or 21% referred through the National Careers Service); the fact that the provider offered the specific course of interest to the learner (18% compared to 10% of those referred through Jobcentre Plus); or the general reputation of the provider (11% compared to 3% of those referred through the National Careers Service).

However, these findings are relatively unsurprising given the primary focus of the National Careers Service (in particular) involves the provision of information, advice and guidance to learners. Table 14 indicates that 25% of learners referred through the National Careers Service chose their provider because of a recommendation specifically from a National Careers Service advisor, while 51% of those respondents referred through Jobcentre Plus mentioned that the recommendation from the Jobcentre Plus advisor was the primary reason for their selection of provider.

Table 14: Reasons for choice of provider – by referral route

| Reason | Self-referred | JCP Adviser | National Careers Service | Other | |---------------------------------------|---------------|-------------|--------------------------|-------| | Convenient location/nearest | 52.3% | 30.2% | 20.7% | 39.0% |

Source: Ipsos MORI and London Economics (2012). Note: Base sample 1,955 In Table 15, we have presented information on the reasons for choice of provider depending on the labour market characteristics of the learners immediately prior to learning commencement. Understandably, convenience factors were considered to be more important than average by those individuals with homecare responsibilities, with 53% of respondents mentioning the convenient location and 12% mentioning convenient times for study. This compares to 47% of those self-employed or in training, and 40% of those who were unemployed, that mentioned the convenience of the location and between 6% and 8% who mentioned the convenient course times.

Recommendations were again important in the decision to select a particular provider, with between 5% and 8% of learners mentioning a friend’s recommendation; between 2% and 4% mentioning a recommendation from a careers advisor, and between 2% and 8% mentioning a recommendation from a family member. Overlapping with the previous information on the impact of different referral routes on provider selection, the analysis indicates that 21% of learners who were unemployed and looking for work immediately prior to starting their course mentioned a recommendation from a Jobcentre Plus or National Careers Service advisor as being a determinant of the choice of provider, compared to 16% of individuals temporarily sick, injured or disabled and 4% of those already in training. Table 15: Reasons for choice of provider – by prior employment status

| Reason | Self employed | Training | Unemployed | Looking after family etc. | Sick/injured/disabled | Retired | Not eligible to work/other | |------------------------------------------------------------------------|---------------|----------|------------|---------------------------|-----------------------|---------|---------------------------| | Convenient location/nearest | 47.4% | 47.3% | 40.1% | 52.7% | 31.1% | 39.1% | 32.6% | | Offered course I wanted | 17.4% | 16.8% | 14.3% | 16.2% | 17.7% | 10.2% | 8.5% | | Has best reputation (general) | 4.2% | 10.5% | 6.8% | 7.5% | 5.7% | 11.7% | 16.0% | | Has best reputation for pass rates | 0.9% | 1.4% | 0.4% | 0.0% | 0.0% | 0.0% | 0.0% | | Has best reputation for my course | 2.0% | 4.9% | 1.5% | 1.6% | 1.8% | 0.0% | 0.0% | | Did a course there previously | 3.4% | 11.4% | 4.4% | 1.3% | 1.9% | 6.0% | 7.6% | | Friends were going there/friend recommended | 8.5% | 6.1% | 6.4% | 5.4% | 4.2% | 12.2% | 0.0% | | Recommended by career advisor/school | 3.1% | 3.1% | 2.3% | 2.3% | 3.6% | 0.0% | 0.0% | | Recommended by National Careers Service /JCP | 6.7% | 4.5% | 20.9% | 7.1% | 16.3% | 4.8% | 13.2% | | Recommended by parents/ family member/ carer | 1.8% | 2.9% | 2.3% | 2.9% | 7.7% | 4.1% | 6.4% | | Offered a course at convenient times for me | 7.6% | 6.3% | 6.4% | 12.5% | 6.9% | 0.0% | 0.0% | | No choice – JCP/National Careers Service chose | 0.7% | 0.0% | 1.3% | 0.3% | 0.9% | 0.0% | 0.0% | | No choice – only one that accepted me | 0.5% | 0.6% | 0.4% | 0.0% | 0.0% | 0.0% | 0.0% | | No choice – no other providers in this area | 0.8% | 1.6% | 1.5% | 1.8% | 1.8% | 10.5% | 14.6% | | Lower cost compared to other providers | 4.8% | 1.4% | 3.3% | 0.9% | 3.4% | 3.8% | 9.7% | | Could study from home/on the internet/self study | 1.6% | 1.6% | 2.0% | 3.9% | 2.3% | 3.6% | 0.0% | | Good facilities/environment/staff | 0.6% | 3.3% | 2.1% | 1.6% | 1.6% | 6.1% | 0.0% | | Helps secure employment/find a job | 0.5% | 0.6% | 0.8% | 0.3% | 0.0% | 0.0% | 0.0% | | Free | 0.4% | 0.5% | 1.8% | 2.1% | 5.3% | 0.0% | 0.0% | | Needed something to do/occupy myself | 0.0% | 0.0% | 0.3% | 0.0% | 0.0% | 0.0% | 0.0% | | Offered good opportunities/future prospects | 0.0% | 0.1% | 0.6% | 0.0% | 0.0% | 0.0% | 0.0% | | Saw advertising/leaflet/open day | 1.3% | 0.9% | 2.8% | 2.6% | 3.1% | 3.6% | 0.0% | | Wanted to gain more knowledge/qualifications | 0.4% | 1.3% | 1.6% | 0.0% | 0.7% | 0.0% | 0.0% | | Wanted to move away/try a new college | 0.8% | 0.6% | 0.1% | 0.0% | 0.0% | 0.0% | 0.0% | | Other specified recommendation | 3.3% | 1.2% | 1.6% | 2.1% | 2.9% | 3.9% | 3.7% | | Other | 1.4% | 2.3% | 2.9% | 2.1% | 0.7% | 0.0% | 0.0% | | Don’t know | 0.0% | 0.9% | 1.1% | 1.1% | 1.5% | 0.0% | 4.5% | | No answer | 0.0% | 0.3% | 1.0% | 0.0% | 3.0% | 0.0% | 0.0% | | Total | 100% | 100% | 100% | 100% | 100% | 100% | 100% |

Source: Ipsos MORI and London Economics (2012). Note: Base sample 1,955 How learners found out about the course and referral

When respondents were asked about how they found out about the learning aim, the information in Table 16 shows that 51% of individuals found out about the training by themselves (i.e. self referred), with a slightly larger proportion of women adopting this self-referral route compared to men (54% compared to 48%).

Table 16: Referral – by gender

| How did you find out about the training (all respondents) | Male | Female | Total | |----------------------------------------------------------|------|--------|-------| | Self-referred | 416 | 581 | 997 | | Jobcentre Plus adviser | 213 | 219 | 431 | | National Careers Service adviser | 29 | 35 | 64 | | Other | 218 | 250 | 468 |

For those indicating referral through JCP, were you

| Referred to National Careers Services adviser | 49 | 38 | 87 | | Referred directly to the college/training provider | 143 | 145 | 288 | | Referred to both | 15 | 27 | 42 | | Don't know/can't remember | 22 | 26 | 48 |

For those indicating referral through JCP, did staff at JCP inform you that you had to attend the/both interview(s) with a National Careers Service adviser/college provider or risk losing your benefit?

| Yes | 59 | 52 | 112 | | No | 139 | 145 | 284 | | Don't know/can't remember | 11 | 15 | 26 |

Before the course has anyone (all respondents)

| Asked you about any qualifications you already had? | 513 | 681 | 1,194 | | Assessed your English, maths or language skills? | 559 | 734 | 1,292 | | Assessed you against some or all of the requirement | 492 | 653 | 1,145 | | Discussed how the training will help you get a job | 488 | 631 | 1,119 |

Who carried out the assessment of your skills and qualifications? (all respondents)

| Training Provider/College Staff/Assessor | 659 | 825 | 1,484 | | School/College Careers visor/Connexions Advisor/ | 44 | 51 | 96 | | National Careers Service advisor | 13 | 19 | 33 | | Jobcentre Plus Adviser | 34 | 39 | 72 | | Other | 50 | 79 | 129 |

How long did you have to wait between being referred and actually attending training (all respondents)

| less than 2 weeks | 438 | 591 | 1,030 | | between 2 and 4 weeks | 236 | 263 | 499 | | between 5 and 7 weeks | 48 | 61 | 109 | | between 8 and 10 weeks | 27 | 33 | 60 | | between 10 to 12 weeks | 26 | 32 | 58 | | more than 3 months | 44 | 57 | 101 | | don't know/can't remember | 55 | 43 | 98 |

Source: Ipsos MORI and London Economics (2012). Note: Base sample 1,955. The two questions relating to the nature of the referral and the potential to receive a sanction were only asked of those individuals referred through Jobcentre Plus (n=431). A quarter of men (24%) and a fifth of women (20%) found out about the course through a Jobcentre Plus adviser with a relatively limited proportion of men and women finding out through the National Careers Service (3%), however, this might underestimate the role of the National Careers Service encouraging individuals to undertake additional learning and training. Of those learners that were referred through a Jobcentre Plus advisor, 21% of men and 16% of women were referred to an interview with a National Careers Service advisor (compared to 62% of men and 61% of women were referred directly to a training provider only and approximately 10% of respondents who were referred to both the National Careers Service and a training provider)\\textsuperscript{12}.

The analysis also suggests that in a quarter (26%) of those cases where an individual was referred by a Jobcentre Plus advisor, the respondent recalled that the Jobcentre Plus advisor had informed the learner that they would risk losing their benefit if they failed to attend the interview with the National Careers Service advisor and/or the learning provider (although a higher proportion of younger learners and learners attempting lower qualification levels recalled being informed of the potential benefit sanction (see Table 17 and Table 18)).

Presented in Table 17, the analysis also illustrates some variation in the route of referral by age, with younger learners more likely to self-refer compared to the population as a whole (56% compared to 53% of 25-39 year olds and 44% of learners aged 40 plus), while older learners were more likely to be referred through a Jobcentre Plus advisor (34% compared to 22% overall). The analysis (presented in Table 18) also indicates that there is more significant variation in the referral route depending on the level of learning aim. Compared to a self-referral rate of 40% for individuals aiming to achieve a Level 1 qualification, the self-referral rate for those attempting a Level 3 qualification stood at over 75%.

**Prior assessment**

Three in five learners (61%) indicated that someone had asked them about the qualifications they were already in possession of before commencing the learning or training, and 66% of learners responded that some assessment of their English, Maths or language skills had been undertaken (Table 16). In only 57% of cases was there any discussion of how the training might help the learner get a job.

Younger learners were marginally more likely to have been asked about prior qualification attainment and been assessed for their English, Maths and languages skills (63% and 67% in Table 17 respectively compared to 58% and 62% for older learners respectively), although were significantly more likely to have had a discussion in relation to the potential employment outcomes associated with gaining the proposed qualification (66% compared to 47% for older learners). In three-quarters of cases, the assessment was undertaken by the training provider.

\\textsuperscript{12} It is important to note that throughout the remainder of the analysis, there are a relatively small proportion of learners indicating their primary referral route was through the National Careers Service and some caution needs to be exercised when considering the differences between sub-samples. Table 17: Referral – by age

| How did you find out about this training (all respondents) | 19-24 | 25-39 | 40+ | |----------------------------------------------------------|-------|-------|-----| | Self-referred | 324 | 55.9% | 393 | 52.9% | 280 | 44.2% | | Jobcentre Plus adviser | 57 | 9.8% | 159 | 21.5% | 215 | 33.9% | | National Careers Service adviser | 12 | 2.0% | 27 | 3.7% | 23 | 3.7% | | Other | 187 | 32.2% | 162 | 21.9% | 116 | 18.3% |

For those indicating referral through Jobcentre Plus, were you

| Referred to interview with a National Careers Service adviser | 19-24 | 25-39 | 40+ | |-------------------------------------------------------------|-------|-------|-----| | Referred directly to the college/training provider | 32 | 51.9% | 104 | 60.7% | 152 | 65.5% | | Referred to both | 10 | 15.6% | 11 | 6.5% | 21 | 9.2% | | Don’t know/can’t remember | 5 | 8.6% | 24 | 14.0% | 19 | 8.1% |

Did staff at Jobcentre Plus inform you that you had to attend the/both interview(s) with a National Careers Service adviser/college provider or risk losing your benefit? (For those indicating referral through JCP)

| Yes | 19-24 | 25-39 | 40+ | |-----|-------|-------|-----| | | 23 | 39.8% | 34 | 22.4% | 55 | 25.7% | | No | 32 | 55.5% | 103 | 68.7% | 150 | 69.6% | | Don’t know | 3 | 4.9% | 13 | 8.8% | 10 | 4.7% |

Before the course has anyone (all respondents)

| Asked you about any qualifications you already had? | 19-24 | 25-39 | 40+ | |-----------------------------------------------------|-------|-------|-----| | | 365 | 63.0% | 459 | 61.9% | 370 | 58.3% | | Assessed your English, maths or language skills? | 389 | 67.2% | 509 | 68.6% | 394 | 62.1% | | Assessed you against some or all of the requirement | 324 | 56.0% | 433 | 58.4% | 388 | 61.2% | | Discussed with you how the training will help you get a job | 381 | 65.7% | 439 | 59.2% | 299 | 47.1% |

Who carried out the assessment of your skills and qualifications? (all respondents)

| Training Provider/College Staff/Assessor | 19-24 | 25-39 | 40+ | |------------------------------------------|-------|-------|-----| | | 442 | 76.4% | 574 | 77.4% | 468 | 73.8% | | School/College Careers visor/Connexions Advisor/ | 52 | 9.0% | 29 | 3.9% | 15 | 2.3% | | National Careers Service advisor | 6 | 1.1% | 14 | 1.8% | 13 | 2.0% | | Jobcentre Plus Adviser | 13 | 2.2% | 30 | 4.1% | 29 | 4.6% | | Other | 28 | 4.8% | 53 | 7.2% | 48 | 7.5% |

How long did you have to wait between being referred and actually attending training (all respondents)

| How long did you have to wait | 19-24 | 25-39 | 40+ | |-------------------------------|-------|-------|-----| | less than 2 weeks | 255 | 44.0% | 387 | 52.2% | 387 | 61.1% | | between 2 and 4 weeks | 156 | 27.0% | 207 | 27.8% | 136 | 21.5% | | between 5 and 7 weeks | 37 | 6.3% | 44 | 5.9% | 28 | 4.5% | | between 8 and 10 weeks | 22 | 3.7% | 23 | 3.0% | 16 | 2.6% | | between 10 to 12 weeks | 25 | 4.4% | 18 | 2.4% | 14 | 2.3% | | more than 3 months | 37 | 6.3% | 34 | 4.6% | 31 | 4.8% | | don’t know | 48 | 8.2% | 29 | 4.0% | 21 | 3.3% |

Source: Ipsos MORI and London Economics (2012). Note: Base sample 1,955. The two questions relating to the nature of the referral and the potential to receive a sanction were only asked of those individuals referred through Jobcentre Plus (n=431).

The analysis also suggests that the extent of appraisal of prior attainment in English, Maths and language skills is positively related to the level of learning aim (Table 18), with learners at Entry level and Level 1 being asked about prior qualifications in 49% and 54% of occasions respectively, compared to 63% of cases at Level 3 and 71% at Level 4. An equivalent increasing relationship between receiving an assessment of English, Maths and language skills and learning aim level was also apparent.

The final element of information presented in Table 16 to Table 18 relates to the amount of time that learners had to wait between being referred and actually attending training. Across the entire sample, 53% of learners responded that they had to wait less than 2 weeks before starting learning, with a further 26% responding that the waiting time was between 2 and 4 weeks. The analysis (presented in Table 17) suggests that younger learners waited longer between being referred and actually starting their training (with only 44% commencing within 2 weeks, compared to 54% for learners aged between 25 and 39 and 61% for learners aged above 40).

Table 18: Referral – by level

| How did you find out about this training (all respondents) | Entry | Level 1 | Level 2 | Level 3 | Level 4 | |-----------------------------------------------------------|-------|---------|---------|---------|---------| | Self-referred | 42.0% | 39.7% | 49.0% | 75.6% | 75.0% | | Job centre plus adviser | 27.2% | 32.3% | 23.5% | 2.9% | 0.0% | | National Careers Service adviser | 4.5% | 3.2% | 3.6% | 1.2% | 0.0% | | Other | 26.4% | 24.9% | 23.9% | 20.3% | 24.5% |

For those indicating referral through Jobcentre Plus, were you

| Referred to interview with National Careers Service adviser | 24.4% | 18.3% | 17.7% | 20.4% | 18.7% | | Referred directly to the college/training provider | 59.3% | 63.9% | 62.7% | 28.6% | 61.9% | | Referred to both | 2.0% | 8.9% | 9.6% | 33.7% | 9.0% | | Don’t know/can’t remember | 14.4% | 8.8% | 10.0% | 17.3% | 10.3% |

Did staff at Jobcentre Plus inform you that you had to attend the/both interview(s) with a National Careers Service adviser/college provider or risk losing your benefit? (For those indicating referral through JCP)

| Yes | 48.2% | 24.8% | 23.5% | 9.8% | 26.4% | | No | 38.6% | 69.9% | 71.5% | 74.4% | 67.4% | | Don’t know | 13.0% | 5.3% | 5.0% | 15.9% | 6.2% |

Before the course has anyone (all respondents)

| Asked you about any qualifications you already had? | 49.0% | 54.2% | 62.3% | 71.8% | 77.0% | | Assessed your English, maths or language skills? | 61.4% | 63.1% | 67.6% | 67.1% | 72.4% | | Assessed you against some or all of the requirement | 46.8% | 53.2% | 61.3% | 61.5% | 87.2% | | Discussed with you how the training will help you get a job | 56.9% | 56.5% | 55.6% | 64.7% | 41.3% |

Who carried out the assessment of your skills and qualifications? (all respondents)

| Training Provider/College Staff/Assessor | 66.7% | 71.1% | 77.0% | 83.2% | 86.7% | | School/College Careers visor/Connexions Advisor/ National Careers Service advisor | 6.6% | 3.2% | 4.1% | 8.3% | 9.7% | | Jobcentre Plus Adviser | 1.3% | 3.5% | 1.5% | 0.2% | 0.0% | | Other | 5.9% | 5.1% | 4.0% | 0.0% | 0.0% |

How long did you have to wait between being referred and actually attending training (all respondents)

| less than 2 weeks | 43.0% | 62.9% | 56.8% | 33.3% | 28.1% | | between 2 and 4 weeks | 29.6% | 22.6% | 25.4% | 27.2% | 31.1% | | between 5 and 7 weeks | 8.2% | 2.4% | 4.7% | 10.6% | 10.2% | | between 8 and 10 weeks | 1.9% | 1.9% | 2.6% | 6.2% | 17.9% | | between 10 to 12 weeks | 3.1% | 3.0% | 1.9% | 6.0% | 7.7% | | more than 3 months | 7.4% | 2.4% | 4.6% | 9.5% | 2.6% | | don’t know | 6.9% | 5.0% | 4.1% | 7.2% | 2.6% |

Source: Ipsos MORI and London Economics (2012). Note: Base sample 1,955. The two questions relating to the nature of the referral and the potential to receive a sanction were only asked of those individuals referred through Jobcentre Plus (n=431).

The analysis also suggests that there is a relatively rapid training start for learners attempting lower levels of qualification (although this does not extend to learners... undertaking Entry Level qualifications). For example, 63% of learners attempting qualifications at Level 1 commenced their training within 2 weeks of referral compared to 33% attempting at Level 3 and 28% at Level 4. Individuals who self-referred were substantially less likely to commence their training as quickly as those who were referred either through Jobcentre Plus or the National Careers Service (47% compared to 64% and 52% respectively (presented in Table 19).

Part of these effects may relate to the fact that the learning aims at lower levels of attainment and those learning aims that respondents were referred to through Jobcentre Plus or the National Careers Service may be of shorter duration and, therefore, operate more frequently compared to learning aims at intermediate of higher levels of attainment, and it might be for this reason that the time between referral and course commencement varies across learners.

| Table 19: Reasons for choice of training – referral route | |----------------------------------------------------------| | **Before the course has anyone** | | *Asked you about any qualifications you already had?* | | Self-referred: 63.9% | | JCP Adviser: 62.6% | | National Careers Service: 58.7% | | Other: 53.8% | | *Assessed your English, maths or language skills?* | | Self-referred: 67.6% | | JCP Adviser: 60.2% | | National Careers Service: 68.5% | | Other: 68.0% | | *Assessed you against some or all of the requirement* | | Self-referred: 59.9% | | JCP Adviser: 53.0% | | National Careers Service: 66.3% | | Other: 59.8% | | *Discussed with you how training will help you get a job*| | Self-referred: 55.1% | | JCP Adviser: 57.5% | | National Careers Service: 53.5% | | Other: 61.9% |

| **Who carried out the assessment of your skills and qualifications?** | |---------------------------------------------------------------------| | Training Provider/College Staff/Assessor: 80.9% | | JCP Adviser: 68.1% | | National Careers Service: 66.9% | | Other: 73.7% | | School/College Careers visor/Connexions Advisor/ | | National Careers Service advisor: 4.6% | | JCP Adviser: 3.3% | | National Careers Service: 4.3% | | Other: 7.0% | | Jobcentre Plus Adviser: 1.3% | | JCP Adviser: 11.5% | | National Careers Service: 0.0% | | Other: 2.1% | | Other: 5.5% | | JCP Adviser: 6.6% | | National Careers Service: 2.4% | | Other: 9.5% |

| **How long did you have to wait between being referred and actually attending training** | |--------------------------------------------------------------------------------------------| | *less than 2 weeks* | | Self-referred: 47.4% | | JCP Adviser: 64.2% | | National Careers Service: 51.8% | | Other: 53.4% | | *between 2 and 4 weeks* | | Self-referred: 25.2% | | JCP Adviser: 24.3% | | National Careers Service: 29.5% | | Other: 26.9% | | *between 5 and 7 weeks* | | Self-referred: 6.9% | | JCP Adviser: 3.7% | | National Careers Service: 6.4% | | Other: 4.5% | | *between 8 and 10 weeks* | | Self-referred: 4.1% | | JCP Adviser: 1.6% | | National Careers Service: 2.2% | | Other: 2.5% | | *between 10 to 12 weeks* | | Self-referred: 3.8% | | JCP Adviser: 1.7% | | National Careers Service: 1.8% | | Other: 2.5% | | *more than 3 months* | | Self-referred: 7.2% | | JCP Adviser: 2.0% | | National Careers Service: 2.9% | | Other: 4.2% | | *don't know* | | Self-referred: 5.5% | | JCP Adviser: 2.6% | | National Careers Service: 5.3% | | Other: 6.0% |

*Source: Ipsos MORI and London Economics (2012). Note: Base sample: 1,955.* The effectiveness of information, advice and guidance

Table 20 and Figure 1 show the effectiveness of the information, advice and guidance provided to learners in terms of ‘net positives’, which is the difference between the proportions of learners describing themselves as either ‘very’ or ‘fairly’ well informed, and those responding ‘not very well’ or ‘not at all’ informed. The results are uniformly positive, although the extent to which this is the case depends on the topic of the advice and (to a lesser extent) the gender of respondent.

Figure 1: Effectiveness of information, advice and guidance (net informed)

Source: Ipsos MORI and London Economics (2012)

The analysis indicates that 79% of men and 80% of women (net) considered themselves to have been well informed in relation to the content of the course and the subjects that would be covered, with between 72% and 76% of men (and 76% and 79% of women) well informed in relation to the amount and standard of the work required of them. Effective information on whether to study the course ‘in one go’ or in units appeared to be less forthcoming with 66% of men and 68% of women considering themselves to have been relatively well informed.

Potentially reflecting the fact that learners appeared to receive less information on how their additional learning and training might result in the learner getting a job, the areas of information advice and guidance where learners considered themselves to be the least well informed (in relative terms) related to how the training/course would assist learners in terms of usefulness in an employment context or the extent to which the training might be able to improve labour market potential (though significantly less so for younger learners). Just over half of respondents (54%) believed that they had been relatively well informed in relation to the labour market potential associated with the training, while just under two-thirds (net) indicated that they received useful advice in relation to the relationship between the training undertaken and how skills might be gained for use in a job.

13 These gender differences are qualitatively similar to those relating to previous analysis (BIS Research Report 104, January 2013 (here)) covering all learners (i.e. those in employment, as well as those not in employment); however, the estimates of ‘net’ positives are several percentage points lower on average compared to the net positive satisfaction ratings posted by the sample of learners including both employed learners and those not in employment. Table 20: Effectiveness of information, advice and guidance by gender

| How well informed in relation to | Male | Female | Total | |---------------------------------|------|--------|-------| | **Content of the course and subjects covered** | | | | | very well informed | 527 | 60.3% | 683 | 63.2% | 1,210 | 61.9% | | fairly well informed | 253 | 28.9% | 285 | 26.3% | 538 | 27.5% | | not very well informed | 65 | 7.5% | 79 | 7.3% | 144 | 7.4% | | not at all informed | 21 | 2.4% | 22 | 2.0% | 43 | 2.2% | | don’t know | 8 | 0.9% | 12 | 1.1% | 20 | 1.0% | | **Amount of work expected in your own time** | | | | | very well informed | 454 | 52.0% | 685 | 63.3% | 1,139 | 58.2% | | fairly well informed | 289 | 33.1% | 256 | 23.7% | 546 | 27.9% | | not very well informed | 84 | 9.7% | 87 | 8.1% | 172 | 8.8% | | not at all informed | 33 | 3.8% | 34 | 3.2% | 68 | 3.5% | | don’t know | 12 | 1.4% | 19 | 1.8% | 32 | 1.6% | | **How course would help gain skills used in a job** | | | | | very well informed | 405 | 46.3% | 566 | 52.3% | 970 | 49.6% | | fairly well informed | 288 | 33.0% | 315 | 29.1% | 603 | 30.9% | | not very well informed | 102 | 11.7% | 116 | 10.7% | 218 | 11.2% | | not at all informed | 54 | 6.1% | 58 | 5.4% | 112 | 5.7% | | don’t know | 25 | 2.9% | 26 | 2.4% | 52 | 2.6% | | **The standard of work expected of you** | | | | | very well informed | 475 | 54.4% | 647 | 59.8% | 1,122 | 57.4% | | fairly well informed | 284 | 32.5% | 316 | 29.2% | 600 | 30.7% | | not very well informed | 64 | 7.3% | 65 | 6.0% | 129 | 6.6% | | not at all informed | 31 | 3.5% | 37 | 3.4% | 68 | 3.5% | | don’t know | 20 | 2.2% | 17 | 1.5% | 36 | 1.9% | | **whether to study the course in units or in one go** | | | | | very well informed | 473 | 54.1% | 628 | 58.1% | 1,101 | 56.3% | | fairly well informed | 236 | 27.0% | 260 | 24.0% | 496 | 25.4% | | not very well informed | 85 | 9.8% | 65 | 6.0% | 150 | 7.7% | | not at all informed | 50 | 5.7% | 82 | 7.6% | 132 | 6.7% | | don’t know | 30 | 3.4% | 47 | 4.3% | 77 | 3.9% | | **Labour market potential** | | | | | very well informed | 357 | 40.8% | 471 | 43.5% | 828 | 42.3% | | fairly well informed | 295 | 33.8% | 351 | 32.4% | 646 | 33.0% | | not very well informed | 122 | 14.0% | 122 | 11.3% | 244 | 12.5% | | not at all informed | 67 | 7.7% | 101 | 9.3% | 168 | 8.6% | | don’t know | 32 | 3.7% | 38 | 3.5% | 70 | 3.6% |

Source: Ipsos MORI and London Economics (2012). Note: Base sample 1,955.

In many respects, there were few differences in the effectiveness of the information, advice and guidance received by age, with younger people generally feeling that they were either well or very well informed on all aspects of the training, including whether to study the course in one go or in units, as well as the labour market potential associated with the course. The analysis also suggests that although individuals aged 25-39 believed they had received more effective information, advice and guidance in terms of the content and amount of work required (compared to either younger or older learners), the findings also demonstrate that younger learners believed that the information received in relation to labour market potential to be the most effective. Although still significantly positive, learners aged 40 plus believed that they received the least effective information, advice and guidance. There was no clear relationship between the perception of how well learners were informed as the level of training increased, with respondents undertaking qualifications at Level 1, Level 2 or Level 3 posting significantly higher ratings compared to those undertaking either Entry Level or Level 4 qualifications.

Table 21: Effectiveness of information, advice and guidance by age and level

| Proportion 'net positives' | 19-24 | 25-39 | 40+ | |---------------------------|-------|-------|-----| | Content of the course and subjects covered | 456 | 78.8% | 611 | 82.3% | 493 | 77.8% | | Amount of work expected in your own time | 417 | 72.0% | 554 | 74.7% | 473 | 74.6% | | How the course would help you gain skills used in a job | 368 | 63.5% | 496 | 66.8% | 380 | 60.0% | | The standard of work expected of you | 464 | 80.1% | 596 | 80.3% | 464 | 73.2% | | Whether to study the course in units or in one go | 391 | 67.5% | 503 | 67.9% | 421 | 66.4% | | Labour market potential | 368 | 63.6% | 402 | 54.2% | 292 | 46.0% |

| Entry | 1 | 2 | 3 | 4 | |-------|---|---|---|---| | Content of the course and subjects covered | 71.5% | 73.5% | 84.0% | 79.2% | 70.4% | | Amount of work expected in your own time | 62.9% | 69.5% | 79.3% | 68.7% | 60.7% | | How the course would help you gain skills used in a job | 54.5% | 62.9% | 64.0% | 69.6% | 49.5% | | The standard of work expected of you | 57.8% | 74.1% | 83.1% | 79.1% | 53.6% | | Whether to study the course in units or in one go | 58.6% | 65.5% | 70.1% | 64.3% | 82.7% | | Labour market potential | 53.7% | 54.0% | 52.2% | 63.2% | 33.7% |

| Self-referred | JCP Adviser | National Careers Service | Other | |---------------|-------------|--------------------------|-------| | Content of the course and subjects covered | 84.0% | 78.8% | 70.1% | 72.9% | | Amount of work expected in your own time | 76.6% | 71.0% | 85.1% | 69.2% | | How the course would help you gain skills used in a job | 64.0% | 65.1% | 68.5% | 60.8% | | The standard of work expected of you | 81.0% | 75.1% | 83.0% | 73.5% | | Whether to study the course in units or in one go | 66.5% | 65.4% | 86.5% | 68.1% | | Labour market potential | 54.4% | 55.0% | 61.3% | 52.5% |

| Continuing | Non-completer | Completed | |------------|---------------|-----------| | Content of the course and subjects covered | 623 | 77.0% | 205 | 72.8% | 732 | 84.7% | | Amount of work expected in your own time | 573 | 70.8% | 187 | 66.7% | 684 | 79.1% | | How the course would help you gain skills used in a job | 523 | 64.5% | 127 | 45.1% | 595 | 68.8% | | The standard of work expected of you | 625 | 77.2% | 195 | 69.5% | 704 | 81.4% | | Whether to study the course in units or in one go | 533 | 65.8% | 159 | 56.5% | 623 | 72.1% | | Labour market potential | 483 | 59.7% | 101 | 36.0% | 477 | 55.2% |

Source: Ipsos MORI and London Economics (2012). Note: Base sample: 1,955

There is a correlation between the degree to which individuals believed they were either well informed or very well informed and course completion (Table 21), however, it is again important to reiterate that the association between the two variables does not imply causation, as it could be the case that those learners failing to complete may have assessed the information, advice and guidance as being not particularly worthwhile as a result of failure to complete. The results presented in Table 21 indicate that those individuals completing their course or training were between 5 and 12 percentage points more likely to indicate they had been well informed in relation to the content of the course; the amount of work necessary; how the course would be of assistance in gaining skills for use in a job; and labour market potential associated with the course. There was a minimal difference in the relative perceptions relating to the standard of the work required and the optimal mode of study. Individuals who self-referred provided more positive feedback in relation to the information, advice and guidance given to them prior to starting their learning: 84% felt well informed about the content of the course (compared to 78% of learners referred by a Jobcentre Plus advisor and 70% referred by a National Careers Service advisor although, again, care needs to be exercised in relation to the sample sizes associated with National Careers Service referral\\textsuperscript{14}. Learners who self-referred also felt better informed on the amount and standard of work expected of them compared to those referred through Jobcentre Plus.

**Reasons for non completion/ factors that would have assisted completion**

For those individuals that failed to complete their course, the survey responses indicate that in just under one half of the cases, the primary reason related to personal or circumstantial considerations, such as family or health related issues (with a greater impact on women than on men). However, this may be somewhat deceptive, as almost 26% of respondents (38) indicated that the reason that they did not complete the learning aim was because they found work.

In 18% of cases, the primary reason was course related (15% for women and 22% for men). Time pressures and workload issues impacted course completion for 20% of men and 19% of women respectively; while in only 6% of cases did respondents mention the fact that financial concerns were the primary reason for their failure to complete.

| Table 22: Main reason for non-completion by gender | |-----------------------------------------------| | **Main reason for non-completion** | Male | Female | Total | | Course related | 27 | 21.6% | 26 | 15.5% | 53 | 18.1% | | Time/workload related | 26 | 20.2% | 32 | 19.5% | 58 | 19.8% | | Personal/ circumstantial | 57 | 45.3% | 85 | 51.6% | 142 | 48.9% | | Financial reasons | 5 | 4.0% | 11 | 6.9% | 16 | 5.6% | | Other | 11 | 8.9% | 11 | 6.7% | 22 | 7.6% |

| What would have enabled you to complete the training | |-----------------------------------------------| | More financial support | 3 | 2.4% | 15 | 9.2% | 18 | 6.3% | | Better guidance/support | 18 | 14.6% | 18 | 11.1% | 36 | 12.6% | | Better course characteristics/ labour market value | 45 | 36.1% | 56 | 34.2% | 101 | 35.0% | | Personal circumstances | 11 | 8.4% | 21 | 12.8% | 32 | 10.9% | | Other | 7 | 5.4% | 12 | 6.6% | 20 | 6.1% | | Don’t know | 12 | 9.1% | 10 | 5.5% | 23 | 7.0% | | No answer | 28 | 20.8% | 31 | 16.6% | 60 | 18.4% |

*Source: Ipsos MORI and London Economics (2012). Note: Base sample: 291.*

As expected, there is some variation depending on the personal characteristics of learners – though sample sizes are increasingly small – so the results are for indicative purposes only. Younger learners were more likely to indicate course related factors as the primary reason for non-completion, with older learners more likely to cite personal or circumstantial reasons for non-completion. This information relating to the reasons for non-completion by qualification level and referral route are presented in Table 23, while in Table 24, we provide some information on the factors which might have assisted completion by age, level of qualification and referral route.

\\textsuperscript{14} The analysis illustrated that of the 62 respondents referred through the National Careers Service, 53 indicated that they had been well or very well informed.

### Table 23: Main reason for non-completion by age and level of qualification

| Main reason for non-completion | 19-24 | 25-39 | 40+ | |-------------------------------|-------|-------|-----| | Course related | 13 | 13 | 27 | | Time/workload related | 6 | 28 | 24 | | Personal/ circumstantial | 15 | 59 | 68 | | Financial reasons | 5 | 5 | 6 | | Other | 5 | 11 | 7 |

| Entry | Other | 1 | 2 | 3 | 4 | |-------------------------------|-------|------|------|------|------| | Course related | 23.9% | 17.2%| 15.7%| 31.8%| 0.0% | 23.9%| | Time/workload related | 15.0% | 20.8%| 20.0%| 22.4%| 0.0% | 15.0%| | Personal/ circumstantial | 42.5% | 51.1%| 52.1%| 21.9%| 100.0%| 42.5%| | Financial reasons | 4.7% | 4.7% | 4.7% | 18.8%| 0.0% | 4.7% | | Other | 13.9% | 6.1% | 7.4% | 5.2% | 0.0% | 13.9%|

Source: Ipsos MORI and London Economics (2012). Note: Base sample 291

### Table 24: Factors assisting completion - by age, level of qualification and referral route

| 19-24 | 25-39 | 40+ | |-------|-------|-----| | More financial support | 4 | 7 | 7 | | Better guidance/support | 8 | 10 | 19 | | Better course characteristics/ labour market value | 9 | 37 | 55 | | Personal circumstances | 1 | 21 | 10 | | Other | 5 | 9 | 6 | | Don’t know | 7 | 8 | 8 | | No answer | 9 | 24 | 27 |

| Entry | Other | 1 | 2 | 3 | 4 | |-------------------------------|-------|------|------|------|------| | More financial support | 4.7% | 4.9% | 5.7% | 19.2%| 0.0% | 4.7% | | Better guidance/support | 9.7% | 16.6%| 10.4%| 21.2%| 0.0% | 9.7% | | Better course characteristics/ labour market value | 43.4% | 30.1% | 37.9% | 17.6% | 0.0% | 43.4% | | Personal circumstances | 2.9% | 14.8%| 10.9%| 9.3% | 0.0% | 2.9% | | Other | 9.4% | 5.6% | 9.4% | 4.3% | 11.0%| 8.2% | | Don’t know | 2.6% | 19.7%| 2.6% | 7.8% | 8.9% | 5.8% | | No answer | 18.2% | 20.3%| 13.5%| 16.4%| 13.7%|

Source: Ipsos MORI and London Economics (2012). Note: Base sample: 291. Course perceptions

The feedback relating to course perceptions was exceptionally positive. When completers were asked about whether they were satisfied with the course, 93% of women and 88% of men indicated that they were either ‘very satisfied’ or ‘fairly satisfied’; while only 5% of women and 9% of men indicated that they were either ‘fairly’ or ‘very’ dissatisfied.15

Table 25: Course perceptions by gender

| How satisfied were you with course? | Male | Female | Total | |------------------------------------|------|--------|-------| | Very satisfied | 260 | 70.2% | 380 | 73.6% | 639 | 72.2% | | Fairly satisfied | 64 | 17.2% | 99 | 19.2% | 163 | 18.4% | | Neither satisfied nor dissatisfied | 15 | 4.1% | 10 | 1.9% | 25 | 2.8% | | Fairly dissatisfied | 11 | 3.0% | 12 | 2.4% | 23 | 2.6% | | Very dissatisfied | 21 | 5.6% | 13 | 2.6% | 34 | 3.8% | | Don’t know | 0 | 0.0% | 1 | 0.2% | 1 | 0.1% |

| How easy did you find doing the course? | Male | Female | Total | |-----------------------------------------|------|--------|-------| | Very easy | 52 | 14.0% | 40 | 7.7% | 92 | 10.3% | | Fairly easy | 78 | 21.0% | 111 | 21.5% | 189 | 21.3% | | Neither easy nor challenging | 52 | 14.1% | 75 | 14.5% | 127 | 14.3% | | Fairly challenging | 140 | 37.9% | 215 | 41.7% | 356 | 40.1% | | Very challenging | 48 | 13.0% | 72 | 13.9% | 120 | 13.5% | | Don’t know | 0 | 0.0% | 4 | 0.7% | 4 | 0.4% |

Source: Ipsos MORI and London Economics (2012). Note: Base sample: 866.

In Table 26, the equivalent information on course satisfaction is presented depending on the learners' age, the level of qualification and the referral route. Again, these questions were only asked of individuals completing the qualification aim. The analysis suggests that younger learners were marginally less satisfied with their course (although still exceptionally positive generally). Specifically, 84% of younger learners were ‘fairly satisfied’ or ‘very satisfied’, while the comparable estimates for learners aged 25-39 and 40+ was 93% and 91% respectively. The survey also suggests that learners undertaking Entry level, Level 1 or Level 2 qualifications were more likely to be satisfied with their course provision (94%, 88% and 92% respectively compared to 81% at Level 4).

Although there was little difference in the satisfaction ratings depending on whether the learner self-referred or was referred through a Jobcentre Plus advisor (90% satisfaction ratings), learners referred through the National Careers Service provided lower satisfaction ratings (83%) though again, the very small sample sizes limit the robustness of these results.

15 It is very likely that satisfaction depends to an extent on whether the course was completed – or the reasons for non-completion. However, these course perceptions questions were only asked of individuals completing the learning aim. Table 26: Course perceptions - by age, level of qualification and referral route

| | 19-24 | 25-39 | 40+ | |----------------------|-------|-------|------| | **Very satisfied** | 106 | 288 | 245 | | **Fairly satisfied** | 28 | 71 | 64 | | **Neither satisfied nor dissatisfied** | 9 | 5 | 12 | | **Fairly dissatisfied** | 6 | 15 | 3 | | **Very dissatisfied** | 10 | 9 | 16 | | **Don't know** | 0 | 0 | 1 |

| | Entry | 1 | 2 | 3 | 4 | |----------------------|-------|------|------|------|------| | **Very satisfied** | 74.9% | 66.9%| 73.8%| 72.3%| 57.0%| | **Fairly satisfied** | 18.9% | 21.0%| 17.7%| 14.5%| 23.7%| | **Neither satisfied nor dissatisfied** | 1.9% | 3.8% | 2.5% | 3.2% | 6.5% | | **Fairly dissatisfied** | 0.0% | 1.7% | 2.9% | 2.9% | 12.9%| | **Very dissatisfied** | 4.3% | 6.2% | 2.9% | 7.1% | 0.0% | | **Don't know** | 0.0% | 0.4% | 0.1% | 0.0% | 0.0% |

| | Self-referred | JCP Adviser | National Careers Service | Other | |----------------------|---------------|-------------|--------------------------|-------| | **Very satisfied** | 74.6% | 70.2% | 75.9% | 69.6% | | **Fairly satisfied** | 16.2% | 20.5% | 6.9% | 21.5% | | **Neither satisfied nor dissatisfied** | 2.7% | 1.5% | 11.7% | 3.6% | | **Fairly dissatisfied** | 3.2% | 3.1% | 0.0% | 1.4% | | **Very dissatisfied** | 3.3% | 4.3% | 5.5% | 4.0% | | **Don't know** | 0.0% | 0.5% | 0.0% | 0.0% |

Source: Ipsos MORI and London Economics (2012). Note: Base sample: 866.

Course ease

In terms of whether the course was considered challenging, 51% of men and 56% of women thought that the course or training was either ‘very challenging’ or ‘fairly challenging’; while 35% of men and 29% of women indicated that they thought that the course was either ‘very easy’ or ‘fairly easy’ (Table 25). There was some variation in the extent to which learners perceived the difficulty of the training received, with younger learners less likely to indicate that the course was either fairly or very challenging than average, and older learners generally indicating learning aims being more challenging than average. Compared to 40% of learners aged 19-24 indicating a high degree of challenge from their learning aim, the equivalent estimates for learners aged between 25 and 39 stood at 59% and 65% for learners aged 40 plus.

There was also some variation in the perceived challenge of learning aims undertaken depending on the level of the current learning aim attempted. 43% of learners at Entry level indicated the learning aim was either fairly or very easy, compared to 32% at Level 1 and Level 2, 20% at Level 3 and none at Level 4. Although this is unsurprising, it may suggest that some people on Entry level qualifications were not being adequately assessed. The economic and social benefits associated with Further Education and Skills: Learning for the unemployed

Table 27: Course ease - by age, level of qualification and referral route

| | 19-24 | 25-39 | 40+ | |----------------|-------|-------|------| | Very easy | 26 | 37 | 28 | | Fairly easy | 43 | 86 | 59 | | Neither easy nor challenging | 25 | 72 | 29 | | Fairly challenging | 54 | 138 | 164 | | Very challenging | 10 | 53 | 57 | | Don’t know | 0 | 1 | 2 |

| | Entry 1 | Entry 2 | Entry 3 | Entry 4 | |----------------|---------|---------|---------|---------| | Very easy | 20.2% | 14.3% | 8.8% | 3.2% | 0.0% | | Fairly easy | 22.7% | 17.3% | 23.0% | 16.7% | 0.0% | | Neither easy nor challenging | 11.2% | 14.2% | 14.0% | 26.5% | 0.0% | | Fairly challenging | 26.7% | 39.9% | 41.3% | 38.2% | 54.8% | | Very challenging | 19.5% | 13.2% | 12.4% | 15.4% | 45.2% | | Don’t know | 0.0% | 1.1% | 0.3% | 0.0% | 0.0% |

| | Self-referred | JCP Adviser | National Careers Service | Other | |----------------|---------------|-------------|--------------------------|-------| | Very easy | 9.3% | 7.9% | 10.3% | 15.5% | | Fairly easy | 21.2% | 21.4% | 15.8% | 22.0% | | Neither easy nor challenging | 14.8% | 14.1% | 30.9% | 11.3% | | Fairly challenging | 40.0% | 42.2% | 40.9% | 37.6% | | Very challenging | 14.0% | 14.0% | 2.4% | 13.5% | | Don’t know | 0.6% | 0.5% | 0.0% | 0.0% |

Source: Ipsos MORI and London Economics (2012). Note: Base sample: 866.

Economic benefits associated with learning

Employment, job satisfaction and further learning

The survey asked respondents to provide some information on the economic benefits that might have been associated with course completion. Completers were also asked their employment status following the conclusion of their learning aim, which are presented in Table 28. The economic and social benefits associated with Further Education and Skills: Learning for the unemployed

Table 28: Labour market outcome post completion by gender

| Labour market outcome post completion | Male | Female | Total | |--------------------------------------|------|--------|-------| | Yes, paid full time employment (16 hours or more p.w.) | 57 | 69 | 126 | | Yes, paid part-time employment (16 hours or less p.w.) | 42 | 100 | 142 | | Yes, self employment | 14 | 12 | 26 | | Yes, unpaid voluntary employment | 27 | 70 | 97 | | No - I have not yet completed the training/support | 15 | 26 | 40 | | No - although I have completed the training/support | 212 | 236 | 447 | | Can’t remember | 5 | 3 | 7 |

Reasons for not seeking paid employment

- Waiting for the end of the course/result of an application: 34 (26.3%) Male, 36 (17.3%) Female, 69 (20.7%) Total
- Children/Family responsibilities: 7 (5.5%) Male, 66 (32.0%) Female, 73 (21.9%) Total
- Financial: 6 (4.9%) Male, 4 (1.8%) Female, 10 (3.0%) Total
- Lack of confidence/qualifications/experience: 1 (0.5%) Male, 3 (1.6%) Female, 4 (1.2%) Total
- Health issues: 53 (41.7%) Male, 56 (27.3%) Female, 110 (32.8%) Total
- Retired/student/language barrier: 16 (12.8%) Male, 30 (14.4%) Female, 46 (13.8%) Total
- Other: 11 (8.3%) Male, 12 (5.6%) Female, 22 (6.6%) Total

Permanent or temporary employment?

- Permanent: 59 (56.8%) Male, 104 (58.3%) Female, 162 (57.8%) Total
- Temporary: 41 (39.2%) Male, 68 (38.2%) Female, 109 (38.6%) Total
- Not sure: 4 (4.0%) Male, 6 (3.4%) Female, 10 (3.6%) Total

Are you still in this job?

- Still in this employment/job: 104 (71.5%) Male, 222 (84.4%) Female, 326 (79.8%) Total
- This job has ended: 42 (28.5%) Male, 41 (15.6%) Female, 82 (20.2%) Total

How long did this employment last?

- less than 3 months: 22 (59.2%) Male, 15 (41.7%) Female, 37 (50.5%) Total
- more than 3 months but less than 6 months: 11 (30.2%) Male, 12 (34.0%) Female, 23 (32.1%) Total
- more than 6 months, but less than 1 year: 3 (9.0%) Male, 7 (19.9%) Female, 11 (14.4%) Total
- more than a year: 1 (1.6%) Male, 1 (2.8%) Female, 2 (2.2%) Total
- can’t remember: 0 (0.0%) Male, 1 (1.7%) Female, 1 (0.8%) Total

Earnings in most recent job after completion

- Under £10,000 per year: 53 (45.5%) Male, 113 (59.8%) Female, 166 (54.4%) Total
- £10,000-£14,999 per year: 29 (24.9%) Male, 31 (16.6%) Female, 61 (19.8%) Total
- £15,000-£19,999 per year: 11 (9.5%) Male, 6 (3.2%) Female, 17 (5.6%) Total
- £20,000-£24,999 per year: 5 (4.0%) Male, 2 (1.0%) Female, 7 (2.2%) Total
- £25,000 or more per year: 1 (1.2%) Male, 1 (0.3%) Female, 2 (0.7%) Total
- Refused/don’t know: 7 (14.8%) Male, 24 (19.0%) Female, 31 (17.4%) Total

Source: Ipsos MORI and London Economics (2012). Note: Base sample: 866. The question in relation to why respondents were not seeking paid employment was only asked to those completers responding that they were neither employed, self employed or unemployed (n=334). The question asking whether the employment position was permanent or temporary was only asked of those completers who indicated that they were either in full time or part time employment or self employed (n=281). Only individuals who stated that their job had ceased responded to the question in relation to how long this employment had lasted (n=74). Earnings include the stated earnings of individuals in full-time, part-time, or self employment.

The sample of learners was drawn from the 2011/12 ILR which covers the academic year 2011/12, so that individuals who were enrolled on a learning aim in 09/2011 were included as potential survey respondents. The survey of learners took place in March/April 2012, and as such some learners had completed their studies, some had failed to complete or had withdrawn, while some learners were continuing with their studies. As such, at the time of survey response, learners who had completed their learning aim were probably completed their learning aim at most 3 to 6 months previously.

There are large and significant economic benefits associated with undertaking and completing learning and training: 15% of men and 13% of women were in full-time paid employment after the completion of their learning aim, while 11% of men and 20% of women were in part-time work. A further 4% of men and 2% of women were self-employed. Combining these estimates implies that 30% of men and 35% of women were in employment following the completion of their course. A further 7% of men and 13% of women were in voluntary or unpaid employment\\textsuperscript{16}. The information in Table 28 also indicates that the position gained was more often than not permanent in nature (58% of cases compared to 39% of employment opportunities that were temporary) \\textsuperscript{17}).

In addition, there was some degree of employment persistence with 71% of male respondents and 84% of female respondents stating they were still in the same employment position. However, of the 20% of respondents indicating that the job had actually come to an end, 50% indicated that their job duration was less than 3 months with a further 32% indicating the job duration was between 3 and 6 months\\textsuperscript{18}.

When considering the average earnings achieved by those achieving employment following the completion of their learning aim, employment opportunities were associated with relatively low levels of earnings. For men, the annual earnings in the job immediately following completion were less than £10,000 per annum in 45% of cases and between £10,000 and £15,000 in a further 25% of cases, while more than 76% of women achieved annual earnings of less than £15,000 per annum (60% below £10,000 and 16% between £10,000 and £15,000). Earnings in excess of £25,000 were achieved on less than 1% of occasions.

However, against these very positive outcomes, half of completers were not in employment following the completion of their course or training (57% of men and 45% of women). When asked about the reasons for not being in employment, the responses highlight the extent to which learners are either ‘close’ or ‘distant’ from the active labour market. In particular, of those not actively seeking employment, 21% were waiting for the completion of the course or on the results of a job application; however 22% were not seeking employment because of childcare of family responsibilities, with a further 33% citing health reasons for the decision not to actively seek work (42% of men compared to 27% of women). One in seven (14%) indicated that they were either retired, a student or face language barriers. In only 1% of cases do respondents mention that the lack of qualifications or experience affected their jobsearch activities.

At a disaggregated level, the economic outcomes following learning completion are presented by age of learner (Table 29), level of learning aim (Table 30) and referral route (Table 31).

\\textbf{Age of learner}

There were some slight distinctions in the employment outcomes of learners depending on age. Compared to the 30% of completers in employment (14% in full-time employment and 16% in part-time employment), although 29% of younger completers were in employment immediately post completion, the balance between full-time and part time work was more uneven. Specifically, only 9% of completers between the ages of 16 and 24 were in full-time employment, with 20% in part-time employment. The fragility of the employment outcome achieved by younger workers post-completion is also reflected in the proportion

\\textsuperscript{16} Note that of those individuals that stated they were engaged in voluntary work or unpaid work prior to the learning aim, the analysis suggests that approximately 31% were still undertaking voluntary or unpaid work, 20% indicated they were working as an employee; 38% were unemployed; 5% were looking after their home or family, while 4% indicated they were not working either because of temporary or long term illness or disability.

\\textsuperscript{17} Information from the LFS indicates that 94% of employees are in permanent positions while 6% in temporary positions (LFS 2012 Q1).

\\textsuperscript{18} In the wider economy, approximately 7.0% of employees have been with their current employer for less than 6 months, with a further 6.4% employed for with their current employer for between 6 months and 1 year (LFS 2012 Q1). of younger respondents indicating that the job was temporary in nature (55%), stating that the job had ended (31%) or the position had lasted for less than 6 months (95%). This compares to estimates of approximately 35%, 18% and 80% respectively for workers aged above 25.

Table 29: Labour market outcome post completion by age

| Labour market outcome post completion | 19-24 | 25-39 | 40+ | |--------------------------------------|-------|-------|-----| | Yes, paid full time employment (16 hours or more p.w.) | 14 | 8.6% | 57 | 14.6% | 56 | 16.4% | | Yes, paid part-time employment (16 hours or less p.w.) | 33 | 20.5% | 57 | 14.8% | 53 | 15.4% | | Yes, self employment | 1 | 0.9% | 15 | 3.8% | 10 | 2.9% | | Yes, unpaid voluntary employment | 14 | 8.7% | 42 | 10.9% | 41 | 12.0% | | No - I have not yet completed the training/support | 14 | 9.1% | 21 | 5.5% | 5 | 1.4% | | No - although I have completed the training/support | 81 | 50.9% | 191 | 49.4% | 175 | 51.5% | | Can’t remember | 2 | 1.3% | 4 | 1.0% | 1 | 0.4% |

Reasons for not seeking paid employment

| Reason | 19-24 | 25-39 | 40+ | |--------|-------|-------|-----| | Waiting for the end of the course/result of an application | 41 | 44.2% | 20 | 14.2% | 9 | 8.2% | | Children/Family | 5 | 5.4% | 55 | 39.8% | 13 | 13.0% | | Financial | 9 | 9.1% | 0 | 0.0% | 2 | 1.5% | | Lack of confidence/qualifications/experience | 0 | 0.0% | 1 | 1.0% | 3 | 2.5% | | Health issues | 14 | 14.7% | 51 | 37.2% | 45 | 43.2% | | Retired/student/language barrier | 19 | 19.9% | 5 | 3.6% | 22 | 21.6% | | Other | 6 | 6.6% | 6 | 4.2% | 10 | 10.0% |

Permanent or temporary employment?

| Employment status | 19-24 | 25-39 | 40+ | |-------------------|-------|-------|-----| | Permanent | 21 | 43.3% | 71 | 59.6% | 70 | 62.0% | | Temporary | 26 | 54.7% | 45 | 37.5% | 37 | 33.0% | | Not sure | 1 | 2.1% | 4 | 2.9% | 6 | 5.0% |

Are you still in this job?

| Employment status | 19-24 | 25-39 | 40+ | |-------------------|-------|-------|-----| | Still in this employment/job | 44 | 69.3% | 140 | 78.6% | 142 | 85.2% | | This job has ended | 20 | 30.7% | 38 | 21.4% | 25 | 14.8% |

How long did this employment last?

| Duration | 19-24 | 25-39 | 40+ | |----------|-------|-------|-----| | less than 3 months | 14 | 78.2% | 11 | 33.1% | 12 | 55.5% | | more than 3 months but less than 6 months | 3 | 17.2% | 14 | 42.3% | 6 | 28.0% | | more than 6 months, but less than 1 year | 1 | 4.6% | 7 | 21.6% | 2 | 10.6% | | more than a year | 0 | 0.0% | 1 | 3.0% | 1 | 2.8% | | can’t remember | 0 | 0.0% | 0 | 0.0% | 1 | 2.8% |

Pay - most recent job after completion

| Pay range | 19-24 | 25-39 | 40+ | |-----------|-------|-------|-----| | Under £10,000 per year | 31 | 63.2% | 77 | 57.9% | 58 | 47.0% | | £10,000-£14,999 per year | 11 | 22.7% | 23 | 17.4% | 26 | 21.1% | | £15,000-£19,999 per year | 2 | 3.8% | 4 | 3.3% | 11 | 8.9% | | £20,000-£24,999 per year | 0 | 0.0% | 2 | 1.3% | 5 | 3.9% | | £25,000 or more per year | 0 | 0.0% | 0 | 0.0% | 2 | 1.6% | | Refused/don’t know | 1 | 10.3% | 17 | 20.0% | 12 | 17.4% |

Note: Base sample: 866. The question in relation to why respondents were not seeking paid employment was only asked to those completers responding that they were neither employed, self employed or unemployed (n=334). The question asking whether the employment position was permanent or temporary was only asked of those completers who indicated that they were either in full time or part time employment or self employed (n=281). Only individuals who stated that their job had ceased responded to the question in relation to how long this employment had lasted (n=74). Earnings include the stated earnings of individuals in either full-time, part-time, or self employment.

Reflecting both the higher incidence of part time working and the generally lower hourly wage rates achieved by younger workers, the analysis also indicates that younger workers were more likely to be in a form of employment offering the lowest annual earnings. Compared to completers aged in excess of 40, where 47% of completers earned less than £10,000 per annum, almost two-thirds of younger workers were in this earnings bracket.

There were also some very noticeable differences between completers in terms of their reasons for not actively searching for paid employment. For younger completers, the most common reason for not seeking paid employment was that they were waiting for the results of a job application (44%), while for completers aged between 25 and 39, the most common reason related to either home/domestic responsibilities or health related reasons (40% and 38% respectively). In contrast, for older completers, the most common reason cited was health related reasons (43%).

**Level of learning aim**

Replicating the analysis by level of learning aim shows some interesting variation. As might be expected, for individuals undertaking and completing higher qualification levels, the level of employment increased steadily, both in terms of full-time employment, but also in terms of the probability of being self-employed.

However, interestingly, the analysis appears to demonstrate that completers with lower levels of qualification attainment were as likely (or more likely) than average to be in a permanent position. The analysis also shows that there is some degree of variation in the extent to which learners were still in the employment position achieved immediately post completion, with 85% of completers at Entry level stating they were still in the position, compared to 73% of learners at Level 1 and 81% of learners at Level 2. However, the analysis does demonstrate that for those individuals for whom the employment position had ended, there was a negative relationship between level of learning aim and employment duration. In particular, approximately 90% of Entry Level completers indicated the position had lasted for less than 6 months, compared to 83% at Level 1, 82% at Level 2 and 65% at Level 3.

In terms of earnings, compared to 55% of learners at an aggregate level achieving earnings of less than £10,000 per annum, the analysis suggests that there is minimal variation around the mean, though it does appear to be the case that higher levels of learning attainment are associated with higher earnings outcomes post completion. Specifically, the information contained in Table 30 suggests that compared to the 59% of learners undertaking Level 1 learning aims, 54% of respondents undertaking Level 2 learning aims achieved annual salaries of less than £10,000, while 50% of learners at Level 3 achieved this earnings outcome. Table 30: Labour market outcome post completion by level of qualification

| Labour market outcome post completion | Entry | 1 | 2 | 3 | 4 | |--------------------------------------|-------|-----|-----|-----|-----| | Yes, paid full time employment (16 hours or more p.w.) | 10.2% | 15.7% | 14.2% | 12.7% | 18.3% | | Yes, paid part-time employment (16 hours or less p.w.) | 8.5% | 12.5% | 18.0% | 15.9% | 5.4% | | Yes, self employment | 10.8% | 1.2% | 2.5% | 3.9% | 16.1% | | Yes, unpaid voluntary employment | 9.8% | 12.9% | 9.7% | 18.1% | 25.8% | | No - I have not yet completed the training/support | 7.2% | 2.7% | 4.6% | 7.1% | 15.1% | | No - although I have completed the training/support | 49.7% | 54.0% | 50.9% | 35.8% | 20.4% |

Reasons for not seeking paid employment

| Reason | Entry | 1 | 2 | 3 | 4 | |--------|-------|-----|-----|-----|-----| | Waiting for the end of the course/result of an application | 13.5% | 10.5% | 16.0% | 50.4% | 0.0% | | Children/Family | 6.1% | 25.8% | 26.1% | 10.8% | 71.4% | | Financial | 8.0% | 0.0% | 2.6% | 4.6% | 0.0% | | Lack of confidence/qualifications/experience | 0.0% | 1.0% | 1.8% | 0.0% | 0.0% | | Health issues | 33.9% | 40.8% | 35.7% | 15.9% | 28.6% | | Retired/student/language barrier | 26.3% | 16.2% | 12.2% | 10.2% | 0.0% | | Other | 12.2% | 5.4% | 5.6% | 8.3% | 0.0% |

Permanent or temporary employment?

| Type | Entry | 1 | 2 | 3 | 4 | |------|-------|-----|-----|-----|-----| | Permanent | 59.2% | 60.0% | 59.3% | 31.7% | 0.0% | | Temporary | 40.8% | 33.9% | 38.1% | 59.3% | 78.3% | | Not sure | 0.0% | 6.1% | 2.6% | 8.1% | 26.1% |

Are you still in this job?

| Status | Entry | 1 | 2 | 3 | 4 | |--------|-------|-----|-----|-----|-----| | Still in this employment/job | 84.7% | 72.9% | 80.6% | 84.7% | 100.0% | | This job has ended | 15.3% | 27.1% | 19.3% | 14.9% | 0.0% |

How long did this employment last?

| Duration | Entry | 1 | 2 | 3 | 4 | |----------|-------|-----|-----|-----|-----| | less than 3 months | 65.5% | 62.5% | 43.6% | 65.5% | 50.5% | | more than 3 months but less than 6 months | 34.5% | 21.0% | 38.6% | 0.0% | 32.1% | | more than 6 months, but less than 1 year | 0.0% | 13.5% | 16.5% | 0.0% | 14.4% | | more than a year | 0.0% | 0.0% | 1.3% | 34.5% | 2.2% | | can't remember | 0.0% | 3.0% | 0.0% | 0.0% | 0.8% |

Pay - most recent job after completion

| Pay | Entry | 1 | 2 | 3 | 4 | |-----|-------|-----|-----|-----|-----| | Under £10,000 per year | 32.3% | 59.4% | 54.5% | 50.0% | 84.2% | | £10,000-£14,999 per year | 21.1% | 19.8% | 20.7% | 8.0% | 0.0% | | £15,000-£19,999 per year | 5.6% | 8.2% | 4.6% | 8.0% | 15.8% | | £20,000-£24,999 per year | 11.2% | 2.6% | 1.5% | 0.0% | 0.0% | | £25,000 or more per year | 0.0% | 0.0% | 0.9% | 0.0% | 0.0% | | Refused/don't know | 30.4% | 10.1% | 17.6% | 34.1% | 0.0% |

Note: Base sample: 866. The question in relation to why respondents were not seeking paid employment was only asked to those completers responding that they were neither employed, self employed or unemployed (n=334). The question asking whether the employment position was permanent or temporary was only asked of those completers who indicated that they were either in full time or part time employment or self employed (n=281). Only individuals who stated that their job had ceased responded to the question in relation to how long this employment had lasted (n=74). Earnings include the stated earnings of individuals in either full-time, part-time, or self employment.

Referral route

Finally, in terms of referral route, the analysis suggests that the average employment rate post completion amongst individuals who self-referred was marginally below average, while the average employment rate amongst completers referred through the National Careers Service or Jobcentre Plus was marginally above average (34% and 35% respectively compared to 30% overall); however, the incidence of full-time work achieved by learners referred through Jobcentre Plus was substantially greater than for those individuals referred through the National Careers Service.

Although again dependent on very small sample sizes, the analysis suggests that completers referred through the National Careers Service were more likely to be in permanent employment (81% compared to 69% for Jobcentre Plus referred learners and 58% overall) and more likely to be still in the position (91% compared to 79% for Jobcentre Plus referred learners and 80% overall). Re-iterating these relatively positive outcomes, as well as the positive outcomes achieved by Jobcentre Plus referred learners, the analysis in Table 31 also suggests that the employment positions achieved by Jobcentre Plus referred learners have a slightly longer duration (27% of positions lasting more than 6 months compared to 17% overall).

Table 31: Labour market outcome post completion by referral route

| Labour market outcome post completion | Self-referred | JCP Adviser | National Careers Service | Other | |--------------------------------------|--------------|-------------|--------------------------|-------| | Yes, paid full time employment (16 hours or more p.w.) | 12.8% | 20.3% | 15.1% | 9.0% | | Yes, paid part-time employment (16 hours or less p.w.) | 16.0% | 14.8% | 29.2% | 16.1% | | Yes, self employment | 3.5% | 2.8% | 0.0% | 2.5% | | Yes, unpaid voluntary employment | 12.4% | 9.7% | 11.3% | 9.7% | | No - I have not yet completed the training/support | 5.3% | 1.3% | 4.8% | 7.1% | | No - although I have completed the training/support | 49.4% | 50.0% | 39.9% | 54.7% |

Reasons for not seeking paid employment

- Waiting for the end of the course/result of an application: 23.9% JCP, 8.0% Self-referred, 10.3% National Careers Service, 21.1% Other
- Children/Family: 22.3% JCP, 21.2% Self-referred, 21.5% National Careers Service, 21.6% Other
- Financial: 2.4% JCP, 0.0% Self-referred, 0.0% National Careers Service, 5.8% Other
- Lack of confidence/qualifications/experience: 1.7% JCP, 1.7% Self-referred, 0.0% National Careers Service, 0.0% Other
- Health issues: 28.0% JCP, 56.6% Self-referred, 53.3% National Careers Service, 30.0% Other
- Retired/student/language barrier: 13.9% JCP, 7.7% Self-referred, 0.0% National Careers Service, 17.6% Other
- Other: 7.8% JCP, 5.2% Self-referred, 15.0% National Careers Service, 3.9% Other

Permanent or temporary employment?

- Permanent: 47.5% JCP, 68.8% Self-referred, 81.5% National Careers Service, 54.1% Other
- Temporary: 50.6% JCP, 26.0% Self-referred, 18.5% National Careers Service, 40.6% Other
- Not sure: 2.0% JCP, 5.1% Self-referred, 0.0% National Careers Service, 5.2% Other

Are you still in this job?

- Still in this employment/job: 81.2% JCP, 79.4% Self-referred, 91.1% National Careers Service, 74.9% Other
- This job has ended: 18.8% JCP, 20.6% Self-referred, 8.9% National Careers Service, 25.1% Other

How long did this employment last?

- less than 3 months: 53.2% JCP, 45.2% Self-referred, 0.0% National Careers Service, 57.4% Other
- more than 3 months but less than 6 months: 30.9% JCP, 28.6% Self-referred, 100.0% National Careers Service, 33.5% Other
- more than 6 months, but less than 1 year: 15.9% JCP, 20.7% Self-referred, 0.0% National Careers Service, 3.4% Other
- more than a year: 0.0% JCP, 2.5% Self-referred, 0.0% National Careers Service, 5.7% Other
- can't remember: 0.0% JCP, 2.5% Self-referred, 0.0% National Careers Service, 0.0% Other

Pay - most recent job after completion

- Under £10,000 per year: 59.5% JCP, 49.3% Self-referred, 65.7% National Careers Service, 49.7% Other
- £10,000-£14,999 per year: 17.9% JCP, 21.6% Self-referred, 29.9% National Careers Service, 18.4% Other
- £15,000-£19,999 per year: 5.2% JCP, 6.8% Self-referred, 0.0% National Careers Service, 5.8% Other
- £20,000-£24,999 per year: 1.5% JCP, 2.1% Self-referred, 4.5% National Careers Service, 3.1% Other
- £25,000 or more per year: 0.5% JCP, 0.6% Self-referred, 0.0% National Careers Service, 1.2% Other
- Refused/don't know: 15.4% JCP, 19.6% Self-referred, 0.0% National Careers Service, 21.8% Other

Note: Base sample: 866. The question in relation to why respondents were not seeking paid employment was only asked to those completers responding that they were neither employed, self employed or unemployed (n=334). The question asking whether the employment position was permanent or temporary was only asked of those completers who indicated that they were either in full time or part time employment or self employed (n=281). Only individuals who stated that their job had ceased responded to the question in relation to how long this employment had lasted (n=74). Earnings include the stated earnings of individuals in either full-time, part-time, or self employment.

One final point emerging from the data analysis is the prevalence of health issues apparently preventing learners referred through Jobcentre Plus or the National Careers Service from seeking paid employment. Compared to the 28% of self-referred completers indicating that health issues prevented them from seeking paid employment, for completers referred through Jobcentre Plus or the National Careers Service, the equivalent proportions were almost double (56% and 53% respectively).

**Current economic status**

Respondents were also asked to indicate their current economic status(^{19}). The information in Table 32 indicates that at the time of the survey, 21% of learners were in employment, with a further 3% being self employed and 4% engaged in voluntary activity. 46% of respondents were currently unemployed and actively seeking work, with the remaining 27% of respondents indicating that they were economically inactive (11% in training; 5% looking after family; 5% either sick, injured or disabled, while a further 1% had retired).

| Current employment status | Male | Female | Total | |---------------------------|------|--------|-------| | Employed | 163 | 176 | 339 | | Self employed | 26 | 19 | 45 | | Undertaking voluntary work| 25 | 46 | 71 | | Training | 85 | 99 | 185 | | Unemployed and looking for work | 387 | 353 | 740 | | Looking after family etc. | 8 | 75 | 83 | | Sick/injured/disabled | 38 | 45 | 83 | | Retired | 9 | 14 | 23 | | Something else (incl. unemployed not looking for work) | 21 | 31 | 52 |

**Table 32: Current employment status by gender**

The analysis presented in Table 33 provides some indication of the employment outcomes of learners prior to the commencement of the learning aim alongside their current economic status(^{20}).

| Current employment status | (EMP) | (SE) | (VOL) | (E/T) | (U) | (LAF) | (S/I/D) | (RET) | (OTH) | |---------------------------|-------|------|-------|-------|-----|-------|---------|-------|-------| | Self employed | 12.7% | 65.5%| 5.5% | 0.0% | 11.4%| 0.0% | 0.0% | 4.5% | 0.0% | | Voluntary Work | 20.0% | 2.2% | 30.8% | 0.0% | 37.9%| 5.3% | 3.9% | 0.0% | 0.0% | | Education/Training | 25.9% | 1.0% | 2.9% | 24.5% | 37.3%| 1.9% | 1.4% | 0.7% | 4.4% | | Unemployed | 22.2% | 2.8% | 2.4% | 4.9% | 59.4%| 2.1% | 3.1% | 0.4% | 2.8% | | Looking after family etc. | 9.3% | 1.8% | 8.0% | 13.6% | 30.6%| 32.1% | 0.4% | 1.0% | 3.2% | | Sick/injured/disabled | 8.5% | 0.0% | 2.0% | 4.6% | 19.8%| 0.0% | 61.6% | 1.5% | 2.0% | | Retired | 0.0% | 0.0% | 4.4% | 0.0% | 4.4% | 0.0% | 0.0% | 92.0% | 0.0% | | Other | 12.7% | 65.5%| 5.5% | 0.0% | 11.4%| 0.0% | 0.0% | 4.5% | 0.0% |

**Table 33: Previous and current employment status**

(^{19}) A high proportion of respondents are still in the same employment position as when competing the course, there will be some degree of overlap between the results presented here and in the previous section; however, completers and non-completers, as well as individuals still continuing their learning aim were asked this series of questions, thereby increasing the potential sample and the robustness of the findings.

(^{20}) See footnote Error! Bookmark not defined. for a detailed description of the time between learning aim completion and response to survey. The analysis indicates that of those that were self-employed, 65% were still in this position, 11% were currently unemployed and looking for work and 12% are now employed. Of those that were training, 25% are currently in training; 26% are in employment and 37% are unemployed and looking for work. Of those that were unemployed and looking for work prior to commencing their learning aim, 59% were currently unemployed; with 22% moving from unemployment to employment; 3% moving to self-employment and 5% in training.

In terms of the occupational nature of the employment achieved, 24% of men and 15% of women indicated that they were in elementary occupations, with a further 9% of men and 2% of women stating that they were process, plant and machine operatives. The largest proportions of learners in employment were engaged in care and leisure occupations (18%), sales and customer service roles (16%) and administrative and secretarial positions (15%). Only 4% of respondents (predominantly men) stated that they were employed in skilled trades’ occupations.

| Table 34: Occupation of employment gender – most recent job | |-----------------------------------------------------------| | Male | Female | Total | | Elementary occupations | 28 | 29 | 56 | 18.4% | | Process, plant and machine operatives | 10.6 | 4 | 15 | 4.9% | | Sales and customer service occupations | 15.6 | 33 | 48 | 15.8% | | Caring, leisure and other service occupations | 10.3 | 46 | 56 | 18.2% | | Skilled trades occupations | 9.9 | 1 | 11 | 3.6% | | Administrative and secretarial occupations | 5.3 | 42 | 47 | 15.4% | | Associate professional and technical occupations | 5.4 | 5 | 11 | 3.5% | | Professional occupations | 2.6 | 15 | 18 | 5.8% | | Managers, directors and senior officials | 1.4 | 5 | 6 | 1.9% | | Other | 27.6 | 10 | 38 | 12.4% |

Source: Ipsos MORI and London Economics (2012). Note: Base sample: 306.

There were some differences in the economic outcomes achieved by respondents depending on the age of the learner. As presented in Table 35, younger learners are more likely than average to be currently in employment (27% compared to 21% overall), while also less likely to be unemployed (39% compared to 45% overall).

| Table 35: Current employment status by age | |-------------------------------------------| | Current employment status | 19-24 | 25-39 | 40+ | | Employed | 141 | 110 | 89 | 18.1% | | Self employed | 5 | 14 | 26 | 5.2% | | Undertaking voluntary work | 13 | 43 | 15 | 3.0% | | Training | 121 | 46 | 18 | 3.6% | | Unemployed and looking for work | 206 | 289 | 245 | 49.7% | | Looking after family etc. | 5 | 51 | 27 | 5.5% | | Sick/injured/disabled | 10 | 33 | 41 | 8.3% | | Retired | 1 | 0 | 22 | 4.4% | | Something else (incl. unemployed not looking for work) | 25 | 16 | 11 | 2.2% |

Source: Ipsos MORI and London Economics (2012). Note: Base sample: 1,620

In addition, there were significantly higher proportions of younger people less distant from the labour market in the sense that only 2% indicated that they were either temporarily or permanently sick or disabled (compared to 5% more generally). The other main category accounting for the activities of younger people related to the 23% currently undertaking additional qualifications or training, which is approximately three times as high as those aged between 25 and 39.

The level of qualification studied was a key determinant of the economic outcomes of learners. Individuals studying Entry level qualifications achieved a 19% employment rate (including the self-employed), compared to an employment rate of 31% for those studying Level 3 qualifications and 41% for those respondents studying Level 4 qualifications. As expected, the level of being unemployed and looking for work appears to be decreasing with the level of qualification, with respondents studying Level 3 qualifications more than 21 percentage points less likely to be currently unemployed and looking for work than those studying an Entry level qualification and 11 percentage points more likely to be both in employment or undertaking further training.

Table 36: Current employment status by level of qualification

| Current employment status | Entry | 1 | 2 | 3 | 4 | |-------------------------------------------|-------|-----|-----|-----|-----| | Employed | 16.9% | 19.9% | 19.4% | 28.7% | 23.1% | | Self employed | 2.4% | 2.1% | 2.9% | 2.6% | 17.9% | | Undertaking voluntary work | 1.9% | 3.0% | 6.0% | 2.7% | 9.0% | | Training | 10.7% | 7.3% | 9.6% | 22.0% | 0.0% | | Unemployed and looking for work | 55.0% | 50.6% | 46.2% | 33.6% | 38.8% | | Looking after family etc. | 3.5% | 5.1% | 6.1% | 3.3% | 3.7% | | Sick/injured/disabled | 4.0% | 6.7% | 5.9% | 1.7% | 7.5% | | Retired | 3.0% | 1.6% | 1.4% | 0.7% | 0.0% | | Something else (incl. unemployed not looking for work) | 2.6% | 3.6% | 2.6% | 4.8% | 0.0% |

Source: Ipsos MORI and London Economics (2012). Note: Base sample: 1,620.

Respondents who indicated that they had self-referred were in employment in 25% of cases and unemployed in 42% of cases. This compares to estimates of employment and unemployment of 21% and 62% respectively for those referred through Jobcentre Plus (probably reflecting the lower job readiness of those learners referred through Jobcentre Plus and the greater level of prior attainment and employment experience of those who self-referred).

Table 37: Current employment status by referral route

| Current employment status | Self-referred | JCP Adviser | National Careers Service adviser | Other | |-------------------------------------------|---------------|-------------|----------------------------------|-------| | Employed | 22.6% | 18.7% | 24.2% | 18.9% | | Self employed | 2.9% | 2.0% | 9.1% | 2.5% | | Undertaking voluntary work | 3.7% | 3.1% | 5.1% | 6.6% | | Training | 12.7% | 3.9% | 10.4% | 14.9% | | Unemployed and looking for work | 42.2% | 62.0% | 33.3% | 41.0% | | Looking after family etc. | 6.4% | 2.6% | 1.3% | 4.9% | | Sick/injured/disabled | 4.1% | 4.9% | 11.0% | 6.8% | | Retired | 1.7% | 0.3% | 2.1% | 1.7% | | Other | 3.8% | 2.4% | 3.4% | 2.6% |

Source: Ipsos MORI and London Economics (2012). Note: Base sample: 1,620. However, the analysis also suggests that there are relatively positive outcomes associated with referral through National Careers Service (though again significant caution needs to be exercised as a result of the small sample sizes). These respondents indicate that they were in employment in 24% of cases; self employed in 9% of cases; engaged in training in 10% of cases; and unemployed and looking for work in 33% of cases.

We have also presented the employment outcomes of learners depending on whether they had completed the learning aim, withdrawn or were currently continuing with the learning aim. The analysis in Table 38 illustrates that 34% of non-completers were either in employment of self employed, compared to 28% who were still continuing their learning aim and 35% who had completed the course. The level of being unemployed and looking for work did not differ substantially across the three groups (between 37% and 39%), although there was a significantly higher proportion of non-completers indicating that they were economically inactive because of childcare responsibilities and sickness or disabilities (6% and 10% respectively) compared to those learners that had completed (4% in each category).

Table 38: Current employment status by completion status

| Current employment status | Continuing | Non-completer | Completer | |-------------------------------------------|------------|---------------|-----------| | Employed | 201 | 85 | 268 | | Self employed | 24 | 11 | 32 | | Undertaking voluntary work | 42 | 10 | 95 | | Training | 132 | 11 | 45 | | Unemployed and looking for work | 314 | 105 | 334 | | Looking after family etc. | 37 | 16 | 31 | | Sick/injured/disabled | 24 | 27 | 33 | | Retired | 6 | 5 | 12 | | Something else (incl. unemployed not looking for work) | 29 | 10 | 14 |

Source: Ipsos MORI and London Economics (2012). Note: Base sample: 1,620.

Perceived additionality – would employment outcomes have been achieved anyway?

What is meant by deadweight loss and additionality?

In general economic terms, deadweight loss is a reduction in net economic benefits resulting from an inefficient allocation of resources and is a common concept when assessing government interventions and programmes. In the context of Further Education and Skills, deadweight loss might occur following the introduction of a particular government policy aimed at raising the skills profile of the population, where the intended outcome (i.e. increased training) might have occurred (at least to some extent) in the absence of the government intervention. Deadweight loss occurs as a result of individuals or employers no longer privately financing their own skills acquisition, or those of their workforce, and substituting publicly financed training in its place. Additionality refers to the concept where the government policy specifically induces the desired outcome that would not have occurred in the absence of such intervention.

______________________________________________________________________

21 Although, as presented in the section relating to the reasons for non-completion, 38 respondents indicated that they had not completed the learning aim in question specifically to undertake a position of employment, which is approximately 36% of those non-completers who were in employment at the time of the survey. The analysis presented here asks slightly different questions to learners who are in employment following the completion of their learning aim. Specifically, the survey asked individuals who had completed their qualification aim and who were in employment, whether the training undertaken had had any impact on the likelihood of finding employment. Again, although the sample sizes are particularly small, the analysis suggests that 44% of learners in employment thought that they would have found employment anyway; 35% of eligible respondents indicated that they would have found employment, though not as quickly; while 21% of respondents believe that they would either ‘probably’ or ‘definitely’ not found employment in the absence of the training. The analysis suggests that men were more convinced of their own abilities for finding employment in the absence of training completion (89% compared to 72% of women).

Table 39 also provides information on learners’ perceptions of their employment prospects. Almost 88% of learners (84% of men and 90% of women) indicated that having undertaken training had improved their employment prospects to a greater extent than if they had not completed the training, while the equivalent proportion of respondents recognising the positive impact of training on earnings stood at 66% (60% for men and 71% for women).

Table 39: Deadweight Loss/ Alternatives by gender

| Proportion of completers responding ‘yes’ | Male | Female | Total | |------------------------------------------|------|--------|-------| | I would have found employment anyway | 53 | 77 | 130 | 44.1% | | I would have found employment but not as quickly | 47 | 56 | 103 | 34.8% | | I would probably not have found employment | 6 | 27 | 33 | 11.3% | | I definitely would not have found employment | 6 | 23 | 29 | 9.8% |

Do you feel that having done your training/qualification that it has improved your employment prospects more than if you had not done the training/qualification?

Do you feel that having done your training/qualification it has given you a level of earnings or earnings potential which you wouldn’t have got if you hadn’t done the training/qualification?

Source: Ipsos MORI and London Economics (2012). Note: For the question relating to whether the individual would have achieved employment in the absence of the training, the base sample stands at 295. The total number of respondents to the question on the potential improvement to employment prospects was 849 (excluding “don’t knows”), while there were 827 respondents (excluding don’t knows) to the question on enhanced earnings potential.

Although generally comparable results are presented depending on the age of the learner, Table 40 indicates that learners aged 19-24 were more positive in relation to the impact that their training may have had on their employment and earnings prospects (91% and 78% answering positively compared to 85% and 56% of learners aged 40 plus respectively). Similar outcomes are associated with individuals completing Entry Level

______________________________________________________________________

Note that in this survey we asked respondents who had completed their learning and were in employment about whether they would have been as likely (or as quickly) to gain employment in the absence of the training received. In our previous report (BIS Research Report 104, January 2013 (here)), we asked learners who had either not paid for their training or contributed only a proportion to the full costs whether their decision to undertake training would have been affected by paying the full amount. As such, the assessment of ‘deadweight’ is not comparable between the two studies.

The employment outcome question is a new question that was not asked in previous survey of FE learners. In the previous FE survey we asked learners who did not make a contribution to course fees/made some contribution only whether they would have undertaken the training if they had to pay the full fees. This question was not asked in this survey because the hypothesis was that a significant proportion of unemployed learners were compelled to attend the training. The economic and social benefits associated with Further Education and Skills: Learning for the unemployed qualifications (Table 41); however, the sample available for these learners (as well as learners at Level 3 and Level 4 are particularly small). Despite this, it is interesting to note that learners attempting Level 1 and Level 2 qualifications were more pessimistic about the impact of their training and qualification attainment compared to the population of respondents in general. Although there appears to be an increase in the proportion of respondents indicating that they would definitely have not found employment at Level 3, this is based off an exceptionally small sample(^{23}) and should be treated with some caution.

Table 40: Deadweight Loss/ Alternatives by age

| Proportion of completers responding 'yes' | 19-24 | 25-39 | 40+ | |------------------------------------------|-------|-------|-----| | I would have found employment anyway | 18 | 39.8% | 50 | 39.0% | 62 | 51.1% | | I would have found employment but not as quickly | 19 | 42.9% | 46 | 35.6% | 38 | 31.0% | | I would probably not have found employment | 7 | 15.6% | 18 | 13.7% | 9 | 7.1% | | I definitely would not have found employment | 1 | 1.8% | 15 | 11.5% | 13 | 10.9% |

Do you feel that having done your training/qualification that it has improved your employment prospects more than if you had not done the training/qualification?

| Proportion of completers responding 'yes' | 19-24 | 25-39 | 40+ | |------------------------------------------|-------|-------|-----| | Do you feel that having done your training/qualification it has given you a level of earnings or earnings potential which you wouldn't have got if you hadn't done the training/qualification? | 141 | 91.2% | 329 | 89.4% | 277 | 84.6% |

Source: Ipsos MORI and London Economics (2012). Note: For the question relating to whether the individual would have achieved employment in the absence of the training, the base sample stands at 295. The total number of respondents to the question on the potential improvement to employment prospects was 849 (excluding “don’t knows”), while there were 827 respondents (excluding don’t knows) to the question on enhanced earnings potential.

Table 41: Deadweight Loss/ Alternatives by level of qualification

| Proportion of completers responding 'yes' | Entry | 1 | 2 | 3 | 4 | |------------------------------------------|-------|---|---|---|---| | I would have found employment anyway | 50.3% | 40.2% | 45.6% | 25.4% | 53.8% | | I would have found employment but not as quickly | 43.6% | 39.8% | 34.3% | 23.8% | 0.0% | | I would probably not have found employment | 0.0% | 6.7% | 12.8% | 8.5% | 46.2% | | I definitely would not have found employment | 6.7% | 13.4% | 7.3% | 42.3% | 0.0% |

Do you feel that having done your training/qualification that it has improved your employment prospects more than if you had not done the training/qualification?

| Proportion of completers responding 'yes' | Entry | 1 | 2 | 3 | 4 | |------------------------------------------|-------|---|---|---|---| | Do you feel that having done your training/qualification it has given you a level of earnings or earnings potential which you wouldn't have got if you hadn't done the training/qualification? | 93.4% | 81.4% | 84.1% | 82.4% | 100.0% |

Source: Ipsos MORI and London Economics (2012). Note: For the question relating to whether the individual would have achieved employment in the absence of the training, the base sample stands at 295. The total number of respondents to the question on the potential improvement to employment prospects was 849 (excluding “don’t knows”), while there were 827 respondents (excluding don’t knows) to the question on enhanced earnings potential.

Finally, turning to Table 42, there are limited differences depending on referral route. Respondents who were referred through Jobcentre Plus were marginally more likely to indicate that they would have achieved their employment outcome in the absence of training compared to self-referred learners (or the sample more generally), but were substantially less positive in relation to the potential earnings impact of the training that

(^{23}) There were 53 respondents to this question at Entry Level, 179 at Level 1, 569 at Level 2, 38 at Level 3 and 9 at level 4 (excluding don’t knows). they had received (59% compared to 69% for those self-referring). Respondents that were referred through National Careers Service appeared as likely to indicate that their employment and earnings prospects had improved as a result of the training received (89% and 77% in the case employment and earnings, compared to 84% and 67% for the sample of learners as a whole).

Table 42: Deadweight Loss/ Alternatives by referral route

| Proportion of completers responding ‘yes’ | Self-referred | JCP Adviser | National Careers Service adviser | Other | |------------------------------------------|---------------|-------------|----------------------------------|-------| | I would have found employment anyway | 39.9% | 53.0% | 38.5% | 39.2% | | I would have found employment but not as quickly | 36.4% | 29.4% | 40.0% | 40.1% | | I would probably not have found employment | 14.5% | 9.5% | 22.2% | 4.8% | | I definitely would not have found employment | 9.3% | 8.2% | 0.0% | 16.1% |

Do you feel that having done your training/qualification that it has improved your employment prospects more than if you had not done the training/qualification?

Do you feel that having done your training/qualification it has given you a level of earnings or earnings potential which you wouldn’t have got if you hadn’t done the training/qualification?

Source: Ipsos MORI and London Economics (2012). Note: For the question relating to whether the individual would have achieved employment in the absence of the training, the base sample stands at 295. The total number of respondents to the question on the potential improvement to employment prospects was 849 (excluding “don’t knows”), while there were 827 respondents (excluding don’t knows) to the question on enhanced earnings potential.

The impact of learning on potential progression and further skills acquisition

In addition to the direct economic effect associated with training in the form of enhanced employment and earnings outcomes, the analysis strongly suggests that undertaking training appeared to have a greater positive effect on learners’ views in relation to further learning and training. Specifically, the analysis presented in Table 43 indicates that almost 84% of learners had become more enthusiastic about learning (81% of men and 86% of women). There was also an impact on whether further training and learning might take place (86% of women and 83% of men), as well as an increase in the likelihood that further training would be undertaken to a higher level (80% of women and 78% of men). The aggregate findings support the widely held belief that training leads to further training and acts as a stepping stone to higher and more economically productive skills acquisition.

Although there were relatively limited differences depending on the age of learner, the analysis suggests that younger learners were 5 percentage point more likely to undertake further learning and training and 15 percentage points more likely to undertake further learning at a higher level. Although there was a decline in the positive perceptions across the age spectrum, it was not uniformly the case. Specifically, learners aged between 25 and 39 were the most enthusiastic about learning (86%), the most likely to undertake further learning and training (89%) and the most likely to undertake further learning at a higher level (84%). These outcomes may reflect the fact that these learners were better informed about the impact of their learning on their career prospects and the associated economic value associated with skills acquisition. The economic and social benefits associated with Further Education and Skills: Learning for the unemployed

Table 43: Impact of training on learner training progression

| | Male | Female | Total | |--------------------------------|------------|------------|------------| | Become more enthusiastic about learning | 705 80.7% | 929 85.9% | 1634 83.6% | | More likely to undertake further learning and training | 726 83.1% | 929 85.9% | 1655 84.7% | | More likely to undertake further learning at a higher level | 678 77.6% | 863 79.8% | 1541 78.8% |

| Age Group | Male | Female | Total | |-----------|------------|------------|------------| | 19-24 | 479 82.7% | 641 86.3% | 514 81.1% | | 25-39 | 488 84.2% | 664 89.4% | 504 79.5% | | 40+ | 482 83.2% | 624 84.1% | 436 68.7% |

| Level | Male | Female | Total | |-----------|------------|------------|------------| | Entry | 85.0% | 82.6% | 82.5% | | Level 1 | 86.0% | 85.0% | 85.1% | | Level 2 | 86.0% | 85.0% | 80.9% | | Level 3 | 81.6% | 72.1% | 81.2% | | Level 4 | 81.6% | 72.1% | 81.2% |

| Referral Route | Male | Female | Total | |----------------|------------|------------|------------| | Self-referred | 85.1% | 83.8% | 83.3% | | JCP Adviser | 86.2% | 82.7% | 86.4% | | NCS adviser | 81.6% | 72.1% | 81.2% | | Other | 81.6% | 72.1% | 81.2% |

| Completion Status | Male | Female | Total | |-------------------|------------|------------|------------| | Completers | 700 86.5% | 212 75.5% | 75.5% | | Non-completers | 698 86.3% | 216 76.7% | 76.7% |

Source: Ipsos MORI and London Economics (2012). Base sample: 1,955.

Looking at the information on how the impact of learning on further skills acquisition depends on the level of learning, the findings do not show any clear pattern (especially given the fact that less emphasis should be placed on learners at Level 4 because of small sample sizes). In terms of the probability of undertaking further education and training, or undertaking further education and training at a higher level, there appears to be a diminishing marginal effect, in the sense that the likelihood of undertaking further education decreases as the level of qualification increases (excluding Level 4); however, there is a slightly lower probability of learners at Entry level, Level 1 and Level 2 indicating that they would undertake further education leading to a higher level of qualification compared to learners at Level 3. Fundamentally, the analysis is inconclusive when disaggregated by level of learning aim.

We also considered whether the impact of educational attainment on learning progression was dependent on the referral route. The information in Table 43 suggests that individuals who self referred were more enthusiastic about learning (compared to the average across all learners), while individuals referred through either a Jobcentre Plus advisor or a National Careers Service advisor were as likely to be enthusiastic about learning (83%-84%). There was some divergence between those referred through Jobcentre Plus and National Careers Service in terms of undertaking further of higher learning and training. In particular, individuals referred through the National Careers Service were 3 percentage points more likely to consider undertaking further learning and training (86% compared to 83%), and 10 percentage points more likely to undertake further training at a higher level (82% compared to 72%); however, care should be exercised as a result of the particularly small sample sizes associated with referral through the National Careers Service. Finally, the analysis demonstrates that there were significant differences in the outcomes achieved by learners depending on their completion status. Completers were 11 percentage points more likely to be more enthusiastic about learning (86% compared to 75%), 9 percentage points more likely to consider undertaking further education and training (86% compared to 77%) and 20 percentage points more likely to undertake additional learning at a higher level (84% compared to 64%).

**Wider social benefits associated with learning**

When respondents who had completed their learning aim were asked about a number of issues that were wider in scope than the purely economic, in addition to the very substantial wider social benefits stated by learners as a whole, there were some clear distinctions depending on respondents’ personal characteristics. Table 44 provides information on learners’ responses in aggregate and by gender and suggests that 81% of learners stated that they had gained self-confidence or self-esteem following the training episode, while almost 72% would take on more social work or voluntary work. More than three-in-four learners suggested that the learning aim had helped them make better use of their spare time, while three in ten learners mentioned that the course had enabled them to assist their children with school work. There were some gender differences (especially in relation to the ability to assist children with school work), although in general these are relatively small. Only 5% of learners indicated that the course had had none of the wider economic benefits presented. Three quarters of respondents indicated that they now had a better idea of what to do with their lives, and 66% indicated that their quality of life had improved as a result of undertaking the education and training activity.

| Table 44: Wider economic benefits by gender | Male | Female | Total | |--------------------------------------------|------|--------|-------| | Gained confidence/self esteem as a result of the course | 672 | 76.9% | 910 | 84.2% | 1582 | 80.9% | | More social activities/voluntary work | 610 | 69.8% | 791 | 73.1% | 1401 | 71.6% | | Course enabled to help children with school work | 156 | 17.9% | 439 | 40.6% | 595 | 30.4% | | Better use of spare time/kept active as a result of the course | 645 | 73.9% | 849 | 78.5% | 1494 | 76.4% | | Course helped with health problems/disability | 107 | 12.3% | 98 | 9.0% | 205 | 10.5% | | None of the above | 50 | 5.7% | 46 | 4.2% | 95 | 4.9% | | Got a better idea about what you want to do in your life | 652 | 74.6% | 819 | 75.8% | 1471 | 75.2% | | Improved your quality of life | 559 | 63.9% | 732 | 67.7% | 1291 | 66.0% |

*Source: Ipsos MORI and London Economics (2012). Base sample: 1,955.*

Training appeared to provide some degree of additional direction to younger learners. Compared to the aggregate estimate of 75%, 83% of respondents aged between 19-24 stated that this was the case, while 73% of younger learners indicated that the learning had improved their quality of life (compared with 66% overall).

| Table 45: Wider economic benefits by age | 19-24 | 25-39 | 40+ | |-----------------------------------------|-------|-------|-----| | Gained confidence/self esteem as a result of the course | 458 | 79.1% | 622 | 83.8% | 502 | 79.2% | | More social activities/voluntary work | 441 | 76.1% | 530 | 71.5% | 430 | 67.8% | | Course enabled to help children with school work | 91 | 15.7% | 326 | 43.9% | 179 | 28.1% | | Better use of spare time/kept active as a result of course | 430 | 74.3% | 571 | 76.9% | 493 | 77.8% | The economic and social benefits associated with Further Education and Skills: Learning for the unemployed

Course helped with health problems/disability

| Level | Entry | 1 | 2 | 3 | 4 | |-------|-------|---|---|---|---| | None of the above | 33 | 5.7% | 22 | 3.0% | 40 | 6.3% |

Got a better idea about what you want to do in your life

| Level | Entry | 1 | 2 | 3 | 4 | |-------|-------|---|---|---|---| | None of the above | 33 | 5.7% | 22 | 3.0% | 40 | 6.3% |

Improved your quality of life

| Level | Entry | 1 | 2 | 3 | 4 | |-------|-------|---|---|---|---| | None of the above | 33 | 5.7% | 22 | 3.0% | 40 | 6.3% |

Source: Ipsos MORI and London Economics (2012). Base sample: 1,955.

Although there is some degree of uniformity in the results depending on the level of qualification attempted, the analysis presented in Table 46 highlights the views of learners at Level 1 and Level 2 compared to learners at other levels of qualification attainment. Specifically, learners at these levels were less likely than average to engage in social/voluntary work; less likely to have a better idea of what to do in life; and less likely to respond that the training had improved their quality of life.

Table 46: Wider economic benefits by level of qualification

| Benefit | Level | Entry | 1 | 2 | 3 | 4 | |---------|-------|-------|---|---|---|---| | Gained confidence/self esteem as a result of the course | Entry | 82.0% | 80.3% | 81.7% | 77.2% | 100.0% | | More social activities/voluntary work | Level 1 | 78.7% | 68.1% | 67.0% | 85.8% | 95.9% | | Course enabled to help children with school work | Level 2 | 29.7% | 30.2% | 31.9% | 26.7% | 24.5% | | Better use of spare time/kept active as a result of course | Level 3 | 77.7% | 74.4% | 76.0% | 79.1% | 83.2% | | Course helped with health problems/disability | Level 4 | 18.5% | 13.2% | 8.8% | 7.7% | 10.2% | | None of the above | Level 5 | 2.3% | 6.8% | 5.0% | 3.9% | 0.0% |

Got a better idea about what you want to do in your life

| Benefit | Level | Entry | 1 | 2 | 3 | 4 | |---------|-------|-------|---|---|---|---| | None of the above | 33 | 5.7% | 22 | 3.0% | 40 | 6.3% |

Improved your quality of life

| Benefit | Level | Entry | 1 | 2 | 3 | 4 | |---------|-------|-------|---|---|---|---| | None of the above | 33 | 5.7% | 22 | 3.0% | 40 | 6.3% |

Source: Ipsos MORI and London Economics (2012). Base sample: 1,955.

The analysis in Table 47 suggests that referral route is associated with the wider benefits achieved by learners, though again this may be due to the characteristics of the learners being referred along the different routes, and not the specific referral process, and the results need to be tempered by the relatively few learners referred through the National Careers Service route. Compared to an average of 81% across all learners, the analysis indicates that for those individuals referred through Jobcentre Plus, the proportion indicating that they had gained self-confidence or self-esteem stood at 78%, compared to 82% who self-referred and 88% for those referred through the National Careers Service.

Self-referred learners were 11 percentage points more likely than JCP referred learners to engage in social/voluntary work; 9 percentage point more likely than JCP referred learners to indicate that they made better use of their spare time; but 3 percentage points less likely to indicate that the course had helped them mange their health problems. They were more likely to suggest that the training or course had had some wider social benefit with just 3% stating that it had had no effect (compared to 7% for Jobcentre Plus referred learners but just 1% of National Careers Service referred learners).

In addition, the analysis indicates that self referred learners were 15 percentage points more likely than JCP referred learners to state that the course had given them a better idea of what to do in their life and improved their quality of life by 9 percentage points more than JCP referred learners.24

24 It is not possible to consider the wider economic benefits of learners depending on whether the individual was mandated, as the numbers of respondents is insufficient (8 respondents) The economic and social benefits associated with Further Education and Skills: Learning for the unemployed

Table 47: Wider social benefits by referral route

| Referral route | Self-referred | JCP Adviser | National Careers Service | Other | |--------------------------------|---------------|-------------|--------------------------|-------| | Gained confidence/self esteem as a result of the course | 82.3% | 78.5% | 88.4% | 79.2% | | More social activities/voluntary work | 74.3% | 63.3% | 70.8% | 73.7% | | Course enabled to help children with school work | 32.4% | 30.2% | 28.3% | 26.8% | | Better use of spare time/kept active as a result of the course | 79.4% | 70.5% | 80.9% | 74.8% | | Course helped with health problems/disability | 8.7% | 10.5% | 13.5% | 13.8% | | None of the above | 3.1% | 7.3% | 1.0% | 7.1% | | Got a better idea about what you want to do in your life | 80.6% | 65.6% | 83.9% | 71.5% | | Improved your quality of life | 68.6% | 59.8% | 63.4% | 66.6% |

Source: Ipsos MORI and London Economics (2012). Base sample: 1,955.

Completion of the qualification aim also impacts the wider social benefits associated with learning and training. Presented in Table 48, completers are 10 percentage points more likely than non-completers to respond that they have gained self-confidence or self-esteem; 24 percentage points more likely to undertake social or voluntary work; 7 percentage points more likely to indicate that the training has assisted them in helping their children with their studies; 8 percentage points more likely to respond that they make better use of their spare time; and 6 percentage points less likely to indicate that the training had impacted none of these outcomes. In addition, 78% of completers also mentioned that their quality of life had improved compared to just 53% of non-completers.

Table 48: Wider economic benefits by completion status

| | Completers | Non-completers | Total | |----------------------|------------|----------------|-------| | Gained confidence/self esteem as a result of the course | 666 82.2% | 205 72.9% | 711 82.3% | | More social activities/voluntary work | 644 79.5% | 156 55.4% | 601 69.5% | | Course enabled to help children with school work | 238 29.4% | 64 22.9% | 293 33.9% | | Better use of spare time/kept active as a result of the course | 632 78.1% | 197 70.0% | 665 76.9% | | Course helped with health problems/disability | 88 10.8% | 25 8.8% | 92 10.7% | | None of the above | 31 3.8% | 27 9.5% | 38 4.3% | | Got a better idea about what you want to do in your life | 691 85.4% | 181 64.5% | 599 69.3% | | Improved your quality of life | 631 77.9% | 148 52.8% | 512 59.2% |

Source: Ipsos MORI and London Economics (2012). Base sample: 1,955.

Satisfaction and wellbeing

In a final element of analysis, information was collected on learners' general wellbeing which is reported in Table 49. These questions were asked to half of respondents at random.

The analysis suggests that there are differences between men and women in response to the question “overall, how satisfied are you with life nowadays?” with women generally being more positive about their circumstances compared to men (7.26 compared to 6.52 for completers), although these general wellbeing measures do lag behind the comparable estimates for the general population(^{25}). In response to the question “overall, to what extent do you feel the things you do in your life area worthwhile?”, women also indicated that they were more content, posting an average score of 7.71 compared to 7.05 posted by men (also for completers only).

| Table 49: Wellbeing scores by gender, age level of qualification and referral route | |---------------------------------------------------------------| | How satisfied are you with your life nowadays? | How happy did you feel yesterday? | Overall, how anxious did you feel yesterday? | Overall, to what extent do you feel the things you do in your life are worthwhile? | | Male | 6.52 | 6.59 | 4.14 | 7.05 | | Female | 7.26 | 6.96 | 4.12 | 7.71 | | 19-24 | 7.40 | 7.23 | 3.90 | 7.86 | | 25-39 | 6.93 | 6.74 | 4.11 | 7.24 | | 40+ | 6.48 | 6.44 | 4.35 | 7.21 | | Entry level | 7.54 | 7.63 | 4.55 | 7.84 | | Level 1 | 6.44 | 6.46 | 4.27 | 7.25 | | Level 2 | 6.83 | 6.68 | 3.90 | 7.29 | | Level 3 | 7.51 | 7.13 | 4.46 | 7.79 | | Level 4 | 7.37 | 6.44 | 4.76 | 7.99 | | Self referred | 6.97 | 6.84 | 4.13 | 7.37 | | JCP Advisor | 6.86 | 6.67 | 4.02 | 7.34 | | National Careers Service Advisor | 6.44 | 6.20 | 3.46 | 7.13 | | Other | 6.98 | 6.87 | 4.30 | 7.63 | | Employed/ Self employed | 8.63 | 8.41 | 4.86 | 8.85 | | Unemployed | 7.49 | 7.51 | 5.32 | 8.18 | | Total | 6.93 | 6.79 | 4.13 | 7.42 |

Source: Ipsos MORI and London Economics (2012). Base sample: 965. Note that we have presented the wellbeing scores of just those individuals that are in employment or unemployed. We have not presented information on the scores posted by other groups including those that are sick, disables, in training, looking after family home etc or retired.

The analysis also indicates that younger learners have higher levels of general wellbeing and lower levels of anxiety compared to older learners (7.40 compared to 6.48 in the case of general wellbeing, and 3.90 compared to 4.35 in relation to anxiety levels). Re-iterating a number of previous results relating to the relatively low level of perceived benefits associated with Level 1 and Level 2 qualifications, the results presented in Table 49 suggest that learners completing these levels of qualification have lower than average general wellbeing scores (compared to individuals in possession of Entry level and Level 3 qualifications). Similarly, the extent to which these learners felt the things they did in their lives were worthwhile were amongst the lowest indicated.

(^{25}) In a relatively recent survey administered by the ONS, the mean measure of subjective well being using the same question as adopted in this survey stood at 7.40. See [http://www.ons.gov.uk/ons/rele/mro/news-release/initial-investigation-of-subjective-well-being---ons-opinions-survey/initial-investigation-of-subjective-well-being---ons-opinions-survey-nr.html](http://www.ons.gov.uk/ons/rele/mro/news-release/initial-investigation-of-subjective-well-being---ons-opinions-survey/initial-investigation-of-subjective-well-being---ons-opinions-survey-nr.html) for more information (accessed 16 May 2012) We also considered whether a person's employment status had an impact on general wellbeing measures. We found that learners that were in employment were more likely to provide high scores compared to individuals that are unemployed and looking for work. Specifically, learners that were currently in employment have an average satisfaction score of 8.63 compared to a score of 7.49 for those that were unemployed and looking for work. Similarly, learners that were employed also indicated that they believed that the things that they did in their life were worthwhile (8.85) compared to those learners that were unemployed and looking for work (8.18).

There were more limited differences depending on the route of referral with those respondents self-referring into learning and training posting higher general wellbeing measures compared to those referred through either Jobcentre Plus or the National Careers Service. Similar findings are demonstrated for the other wellbeing measures, although respondents referred to learning by a National Careers Service advisor do post amongst the lowest anxiety measures. Annex 1 Methodological approach

This section provides details on the design and administration of the learner survey.

Survey population and sample frame

The survey population comprised learners who received and/or completed training (irrespective of outcome) but were not in paid employment prior to the learning. The Individual Learner Record (ILR) was used as the sample frame.

Sample size and design

The target sample size was 2,000 interviews. Preparatory work on the sample frame comprised of removing learners who did not give consent to take part in research, duplicate entries, learners identified as deceased and learners without a telephone number.

A stratified random sample was drawn. The stratification variables were: completion status (completed; withdrawn; still studying); funding status (in receipt of YPLA/Skills Funding Agency DLF Funding; no funding); and qualification levels (Entry; Level 1; Level 2; Level 3 or higher).

Questionnaire development and piloting

The questionnaire was designed by Ipsos MORI and London Economics in collaboration with BIS. The questionnaire content was informed by a literature review undertaken as part of a research study into the impact of Further Education learning and a review of previous surveys (BIS Research Report 104, January 2013). The following topic areas (standardised questions were used where possible to enable comparisons with relevant studies commissioned by BIS):

- Learner characteristics including age, gender, ethnicity, English as a first language, disability, learning difficulties, marital and parental status, religion, sexual orientation and highest qualification;
- Prior economic status and perceived barriers to work;
- Current economic activity including employment status, income and benefits status;
- Reasons for choice of course and provider and initial expectations on outcomes of the learning;
- Experience of JobCentre Plus programmes/initiatives and experience of Information, Advice and Guidance (IAG) in relation to the course;
- Reasons for non-completion;
- Outcomes of the learning and perceived benefits (employment-related and wider outcomes including social benefits).

______________________________________________________________________

26 Individuals were identified using variable I37 "Employment status on first day of learning" (all those "Not Employed") were included. The following exclusions were applied: Qualifications at L5 or above; Apprenticeships; Offender learning; Learners aged 16-18 or 65 plus; Funding streams other than "YPLA/Skills Funding Agency DLF Funding" and No Funding; and Non-English residents.

27 Originally, it was thought it would be interesting to look at unfunded learners; however, only 89 responses were achieved so limited the potential for analysis. The questionnaire was piloted with 26 learners. Feedback from the pilot was very positive; participants generally found the survey straightforward and were happy to take part. The average interview length was 21 minutes.

The telephone survey was conducted by Ipsos MORI Telephone Surveys using Computer Assisted Telephone Interviewing (CATI). Fieldwork took place between 20 February and 30 March 2012.

Ipsos MORI Telephone Surveys is a member of the Interviewer Quality Control Scheme (IQCS) and has Market Research Quality Standards Association (MRQSA) quality accreditation. A minimum of ten percent of interviews were monitored by supervisors listening-in to the interviews and checking interviewers’ coding of responses.

Response rates

The adjusted response rate was 52%. The co-operation rate was 65%. There was some variation in response rate by age and Aims Level with lower than average response rate among learners aged 19-39 and those undertaking Entry and Level 1 qualifications.

| Final sample status | Total sample used (N) | Total sample used (%) | Valid sample (%) | |--------------------------------------|-----------------------|-----------------------|------------------| | **Valid sample** | | | | | Achieved interviews | 1,958 | 35 | 52 | | Respondent quit interview | 139 | 2 | 4 | | Refusal | 886 | 16 | 23 | | Leads tried max times/no reply | 631 | 11 | 17 | | Not available during fieldwork | 84 | 1 | 2 | | Wrong language | 77 | 1 | 2 | | **Total valid sample** | 3,774 | 67 | 100 | | **Invalid sample** | | | | | Bad number | 1,184 | 21 | | | Respondent no longer at address | 48 | 1 | | | Duplicate | 4 | 0 | | | Ineligible | 641 | 11 | | | **Total invalid sample** | 1,877 | 33 | | | **Total sample used** | 5,651 | 100 | |

Unadjusted response rate 35 Adjusted response rate 52 Weighting

There was a good match between the sample and population in terms of completion level and funding. Corrective weights were applied for Qualification Level and age (interlocking weights) as well gender and ethnicity. Annex 2 Additional information on sample

Assessment of match and reliability of sample

The comparison of the basic personal characteristics between the sample and the ILR appears positive, with good comparability between the data sources. In the next section, we present some more detail on the socioeconomic characteristics of the sample; however, it is important to note that there are some discrepancies between the sample and the ILR, especially in relation to the information contained in the ILR in respect of completion and achievement, as well as the information relating to the qualification undertaken.

Specifically, although the sample indicates that 558 learners achieved their learning aim, information on these learners from the ILR indicates that 35 learners decided not to continue with their learning aim and did not complete their qualification. In addition, of the 587 learners who failed or withdrew from the designated qualification (from the ILR), 341 responded that they had completed the qualification. The number of learners where there appears to be mismatch in relation to achievement status stands at 376, which is approximately 33% of the sample (excluding those still continuing their qualification).

| Failed/ withdrawn | Achieved | Total | |-------------------|----------|-------| | Decided not to continue | 246 | 35 | 281 | | Completed qualification | 341 | 523 | 864 | | Total | 587 | 558 | 1,145 |

Source: Ipsos MORI and London Economics (2012): s2 - how far have you got with this training/qualification? Note: Base sample – 1,145.

One of the reasons why there may be a degree of mismatch relates to the qualification under consideration. There is often some degree of either recollection error, where learners simply state they completed the learning aim when this was not the case, or learner may not recognise the formal title of their learning aim or if the ILR contains information that is out of date, whereby the learner has completed a specific qualification and gone on to further learning and training (which they respond about in the survey).

The existence of mismatch between the self-reported qualification type and the qualification level reported in the ILR is also suggested by a cross-tab of the two variables, presented in Error! Reference source not found.. Self-reported qualification is reported along the rows, while information on the ILR is available along the columns. Results suggest that in some cases respondents may not be able to accurately identify their qualification, or the fact that they may be referring to a different qualification. The full extent of the mismatch is not readily identifiable, given that for vocational qualifications respondents were also asked to report their qualification type, but not the level. When assessing the nature of the mismatch, it should be remembered that course title from the ILR was clearly stated at the beginning of the interview and all questions were referred to that specific course and qualification. In this respect the mismatch is likely to be mainly explained by the misperception element (with respondents unable to identify their qualification type).

Although this potential mismatch is of importance for analyses based on the ILR, it is of less importance in terms of the current analysis. Data collected from learners will always contain some degree of mismatch from the original data from which the sample is drawn; however, throughout the subsequent analysis, we use the information from the sample of learners only and do not use information from the ILR to supplement the analysis if equivalent information is already available through the survey. We have no reason to believe that there is any methodological weakness associated with this approach.

Table 51: Unemployed learner participation by aggregated qualification level (ILR 2011/12)

| Male | Female | Total | |------|--------|-------| | Entry Level | 1,925 | 2,321 | 4,246 | 100.0% | | Level 1 | 4,202 | 4,746 | 8,948 | 100.0% | | Level 2 | 10,199 | 13,606 | 23,805 | 100.0% | | Level 3 | 3,475 | 3,623 | 7,098 | 100.0% | | Level 4 | 129 | 335 | 464 | 100.0% | | Total | 19,930 | 24,631 | 44,561 | 100.0% |

Sample 874 44.7% 1,081 55.3% 1,955 100.0%

Ipsos MORI and London Economics (2012)

Table 52: Unemployed learner participation by disaggregated qualification level (ILR 2011/12)

| Male | Female | Total | |------|--------|-------| | Entry Level or Other | 1,221 | 1,470 | 2,691 | 100.0% | | SFL Entry Level or Other | 704 | 851 | 1,555 | 100.0% | | SFL L1 | 2,060 | 2,684 | 4,744 | 100.0% | | Award L1 | 1,037 | 1,255 | 2,292 | 100.0% | | Certificate L1 | 524 | 418 | 942 | 100.0% | | Diploma L1 | 170 | 23 | 193 | 100.0% | | BTEC L1 | 88 | 49 | 137 | 100.0% | | NVQ L1 | 18 | 45 | 63 | 100.0% | | Other L1 | 305 | 272 | 577 | 100.0% | | SFL L2 | 3,608 | 5,523 | 9,131 | 100.0% | | Award L2 | 120 | 134 | 254 | 100.0% | | Certificate L2 | 3,720 | 5,851 | 9,571 | 100.0% | | Diploma L2 | 646 | 638 | 1,284 | 100.0% | | BTEC L2 | 39 | 34 | 73 | 100.0% | | NVQ L2 | 526 | 926 | 1,452 | 100.0% | | GCSEs | 180 | 260 | 440 | 100.0% | | Other qualifications at L2 | 1,360 | 240 | 1,600 | 100.0% | | Award L3 | 63 | 47 | 110 | 100.0% | | Certificate L3 | 179 | 372 | 551 | 100.0% | | Diploma L3 | 1,493 | 1,805 | 3,298 | 100.0% | | BTEC L 3 | 984 | 636 | 1,620 | 100.0% | | NVQ L 3 | 94 | 356 | 450 | 100.0% | | GCE A/AS/A2 level | 53 | 60 | 113 | 100.0% | | Other qualifications at L3 | 609 | 347 | 956 | 100.0% | | Level 4 qualifications | 129 | 335 | 464 | 100.0% | | Total | 19,930 | 24,631 | 44,561 | 100.0% |

Sample 874 44.7% 1,081 55.3% 1,955 100.0%

Ipsos MORI and London Economics (2012) Table 53: Unemployed learner participation by aggregated qualification level by region (ILR 2011/12)

| Level | North East | North West | Yorkshire/ Humber | East Midlands | West Midlands | East of England | London | South East | South West | |-------|------------|------------|-------------------|---------------|---------------|----------------|--------|------------|------------| | Entry | 6.6% | 16.6% | 11.1% | 5.2% | 9.2% | 11.4% | 22.4% | 7.8% | 9.8% | | Level 1 | 7.5% | 11.1% | 9.2% | 6.6% | 12.8% | 12.8% | 18.2% | 11.8% | 10.2% | | Level 2 | 5.5% | 12.0% | 10.6% | 5.2% | 11.9% | 11.7% | 18.3% | 13.6% | 11.2% | | Level 3 | 4.8% | 15.5% | 14.2% | 8.0% | 11.3% | 11.6% | 13.6% | 8.9% | 12.0% | | Level 4 | 2.4% | 24.8% | 7.8% | 9.1% | 14.4% | 5.6% | 9.5% | 8.4% | 18.1% | | Total | 5.9% | 12.9% | 10.9% | 6.0% | 11.7% | 11.8% | 17.8% | 11.9% | 11.0% | | Sample | 6.3% | 12.4% | 12.1% | 4.8% | 12.2% | 13.2% | 12.9% | 13.2% | 12.9% |

*Ipsos MORI and London Economics (2012)* Table 54: Unemployed learner participation by disaggregated qualification level by region (ILR 2011/12)

| Qualification Level | North East | North West | Yorkshire/Humber | East Midlands | West Midlands | East of England | London | South East | South West | |---------------------|------------|------------|------------------|--------------|--------------|----------------|--------|------------|------------| | Entry Level or Other| 6.7% | 19.7% | 11.9% | 5.7% | 8.4% | 11.1% | 20.8% | 5.5% | 10.2% | | SFL Entry Level or Other| 6.6% | 11.1% | 9.7% | 4.2% | 10.4% | 11.8% | 25.3% | 11.9% | 9.0% | | SFL L1 | 5.2% | 9.9% | 8.3% | 5.0% | 13.2% | 11.3% | 23.1% | 13.9% | 10.1% | | Award L1 | 5.7% | 13.5% | 9.1% | 9.0% | 11.2% | 14.8% | 11.3% | 13.3% | 12.1% | | Certificate L1 | 25.1% | 9.4% | 11.7% | 9.4% | 12.5% | 13.2% | 4.0% | 3.1% | 11.6% | | Diploma L1 | 3.6% | 5.7% | 11.9% | 7.3% | 26.4% | 0.5% | 33.2% | 4.1% | 7.3% | | BTEC L1 | 0.0% | 16.8% | 7.3% | 3.6% | 2.2% | 46.0% | 19.7% | 3.6% | 0.7% | | NVQ L1 | 22.2% | 20.6% | 3.2% | 1.6% | 1.6% | 0.0% | 30.2% | 20.6% | 0.0% | | Other L1 | 5.5% | 13.0% | 13.0% | 6.6% | 15.6% | 13.9% | 21.3% | 5.9% | 5.2% | | SFL L2 | 5.0% | 10.8% | 8.1% | 4.3% | 11.3% | 13.6% | 22.3% | 14.9% | 9.8% | | Award L2 | 4.7% | 25.6% | 13.8% | 9.1% | 3.5% | 16.5% | 7.1% | 6.7% | 13.0% | | Certificate L2 | 5.9% | 12.3% | 11.6% | 5.1% | 11.5% | 10.6% | 15.4% | 15.7% | 12.0% | | Diploma L2 | 8.5% | 11.4% | 16.0% | 5.2% | 12.9% | 6.6% | 18.1% | 5.5% | 15.7% | | BTEC L2 | 4.1% | 1.4% | 39.7% | 0.0% | 4.1% | 21.9% | 17.8% | 1.4% | 9.6% | | NVQ L2 | 7.0% | 13.3% | 9.4% | 8.2% | 13.8% | 11.0% | 15.4% | 10.3% | 11.7% | | GCSEs | 3.0% | 20.2% | 23.4% | 5.9% | 14.5% | 7.5% | 13.6% | 6.1% | 5.7% | | Other qualifications at L2 | 3.5% | 12.1% | 11.3% | 8.1% | 15.4% | 13.1% | 18.2% | 7.1% | 11.2% | | Award L3 | 9.1% | 7.3% | 26.4% | 2.7% | 2.7% | 14.5% | 5.5% | 6.4% | 25.5% | | Certificate L3 | 4.7% | 19.2% | 18.7% | 9.1% | 10.0% | 15.4% | 6.4% | 7.3% | 9.3% | | Diploma L3 | 5.2% | 15.4% | 14.3% | 7.9% | 11.1% | 11.5% | 13.5% | 10.1% | 11.0% | | BTEC L3 | 2.8% | 16.6% | 12.5% | 8.3% | 14.2% | 11.9% | 15.4% | 7.4% | 10.9% | | NVQ L3 | 6.9% | 12.7% | 10.4% | 9.8% | 14.7% | 12.4% | 16.2% | 6.0% | 10.9% | | GCE A/AS/A2 level | 9.7% | 5.3% | 9.7% | 1.8% | 4.4% | 13.3% | 23.0% | 16.8% | 15.9% | | Other qualifications at L3 | 4.8% | 15.4% | 15.4% | 7.7% | 8.2% | 8.4% | 13.8% | 9.2% | 17.2% | | Level 4 qualifications| 2.4% | 24.8% | 7.8% | 9.1% | 14.4% | 5.6% | 9.5% | 8.4% | 18.1% | | Total | 5.9% | 12.9% | 10.9% | 6.0% | 11.7% | 11.8% | 17.8% | 11.9% | 11.0% |

Sample 6.3% 12.4% 12.1% 4.8% 12.2% 13.2% 12.9% 13.2% 12.9%

Ipsos MORI and London Economics (2012)

### Table 55: Unemployed learner participation by aggregated qualification level by ethnic origin (ILR 2011/12)

| Ethnic Origin | Entry Level | Level 1 | Level 2 | Level 3 | Level 4 | Total | Sample | |---------------|-------------|---------|---------|---------|---------|-------|--------| | White - British | 48.4% | 60.8% | 64.0% | 67.4% | 69.8% | 62.5% | 65.5% | | White - other | 8.2% | 7.2% | 7.4% | 5.1% | 6.5% | 7.1% | 4.5% | | Bangladeshi | 2.4% | 1.3% | 1.1% | 0.8% | 1.3% | 1.2% | 1.4% | | Indian | 2.9% | 2.5% | 2.9% | 1.9% | 2.4% | 2.6% | 3.0% | | Pakistani | 6.4% | 3.9% | 3.5% | 4.5% | 3.4% | 4.0% | 4.2% | | Asian - other | 6.1% | 3.7% | 2.3% | 2.1% | 1.3% | 2.9% | 2.2% | | Black - African | 9.2% | 7.7% | 7.5% | 6.1% | 4.7% | 7.4% | 7.6% | | Black - Caribbean | 2.5% | 3.7% | 3.6% | 2.5% | 2.2% | 3.3% | 3.2% | | Black - other | 1.7% | 1.9% | 1.6% | 1.2% | 0.0% | 1.6% | 1.7% | | Chinese | 1.1% | 0.4% | 0.3% | 0.5% | 0.9% | 0.4% | 0.5% | | Mixed | 3.8% | 3.2% | 2.8% | 3.8% | 3.4% | 3.1% | 3.2% | | Any other | 6.4% | 2.9% | 2.2% | 2.6% | 3.4% | 2.8% | 3.0% | | Unknown/Provided | 1.1% | 0.9% | 0.9% | 1.4% | 0.6% | 1.0% | 0.0% |

*Ipsos MORI and London Economics (2012)* Table 56: Unemployed learner participation by disaggregated qualification level by ethnic origin (ILR 2011/12)

| Qualification Level | White - British | White - other | Bangladeshi | Indian | Pakistani | Asian other | Black African | Black Caribbean | Black other | Chinese | Mixed | Any other | Unknown/Provided | |---------------------|-----------------|---------------|-------------|--------|-----------|-------------|---------------|----------------|-------------|---------|-------|---------|-----------------| | Entry Level/ Other | 49.8% | 7.2% | 2.6% | 2.2% | 6.4% | 6.8% | 8.0% | 1.4% | 1.5% | 1.3% | 4.0% | 7.8% | 1.0% | | SFL Entry Level | 45.9% | 10.0% | 2.0% | 4.2% | 6.5% | 5.0% | 11.2% | 4.4% | 1.9% | 0.6% | 3.4% | 3.8% | 1.1% | | SFL L1 | 52.0% | 9.4% | 1.6% | 3.0% | 5.3% | 5.1% | 9.6% | 4.3% | 2.0% | 0.3% | 3.6% | 3.1% | 0.8% | | Award L1 | 73.0% | 4.5% | 0.8% | 2.2% | 2.9% | 1.8% | 5.8% | 2.4% | 1.3% | 0.3% | 2.1% | 1.7% | 1.1% | | Certificate L1 | 82.0% | 2.5% | 0.2% | 0.7% | 0.7% | 1.1% | 4.4% | 2.4% | 0.8% | 0.2% | 2.3% | 1.5% | 1.1% | | Diploma L1 | 58.0% | 4.1% | 1.6% | 1.0% | 1.6% | 0.0% | 6.2% | 14.0% | 2.6% | 0.5% | 7.3% | 1.6% | 1.6% | | BTEC L1 | 54.7% | 5.1% | 0.0% | 2.9% | 5.1% | 0.7% | 8.8% | 0.7% | 10.9% | 0.0% | 5.1% | 5.8% | 0.0% | | NVQ L1 | 66.7% | 4.8% | 0.0% | 1.6% | 1.6% | 4.8% | 9.5% | 7.9% | 1.6% | 0.0% | 1.6% | 0.0% | 0.0% | | Other L1 | 51.6% | 9.0% | 2.3% | 2.3% | 2.3% | 6.1% | 5.9% | 2.8% | 2.1% | 1.2% | 3.8% | 9.0% | 1.7% | | SFL L2 | 54.6% | 9.2% | 1.6% | 3.5% | 4.4% | 3.3% | 10.2% | 3.9% | 2.1% | 0.2% | 3.3% | 2.7% | 1.0% | | Award L2 | 77.2% | 3.5% | 1.6% | 0.0% | 3.5% | 2.0% | 3.5% | 2.0% | 0.0% | 1.2% | 2.8% | 0.8% | 2.0% | | Certificate L2 | 70.1% | 7.2% | 0.9% | 2.7% | 2.5% | 1.7% | 5.5% | 2.7% | 1.3% | 0.3% | 2.1% | 2.0% | 0.9% | | Diploma L2 | 71.9% | 3.5% | 0.5% | 1.4% | 2.2% | 0.5% | 8.3% | 6.4% | 0.7% | 0.2% | 2.6% | 1.3% | 0.3% | | BTEC L2 | 61.6% | 5.5% | 0.0% | 0.0% | 5.5% | 2.7% | 9.6% | 2.7% | 0.0% | 0.0% | 2.7% | 8.2% | 1.4% | | NVQ L2 | 75.4% | 6.5% | 0.4% | 1.8% | 3.0% | 0.6% | 3.8% | 2.3% | 1.2% | 0.1% | 2.7% | 1.5% | 0.7% | | GCSEs | 48.6% | 3.9% | 2.0% | 4.3% | 12.7% | 4.1% | 11.6% | 2.0% | 0.9% | 0.9% | 4.1% | 3.6% | 1.1% | | Other quals. at L2 | 67.1% | 3.8% | 0.8% | 2.2% | 3.1% | 1.9% | 5.6% | 6.0% | 1.8% | 0.5% | 4.4% | 2.1% | 0.6% | | Award L3 | 71.8% | 3.6% | 1.8% | 0.0% | 10.0% | 0.0% | 1.8% | 2.7% | 0.9% | 0.9% | 4.5% | 1.8% | 0.0% | | Certificate L3 | 76.2% | 4.4% | 0.5% | 1.6% | 5.1% | 0.5% | 1.8% | 2.2% | 1.1% | 0.2% | 2.4% | 1.1% | 2.9% | | Diploma L3 | 67.6% | 5.2% | 0.6% | 1.6% | 3.8% | 2.1% | 6.9% | 2.4% | 1.3% | 0.5% | 3.8% | 2.9% | 1.3% | | BTEC L 3 | 61.5% | 5.7% | 1.0% | 2.2% | 5.5% | 2.9% | 8.1% | 2.9% | 1.2% | 0.7% | 4.4% | 2.5% | 1.4% | | NVQ L 3 | 66.2% | 5.1% | 0.7% | 4.2% | 2.4% | 2.7% | 3.3% | 2.2% | 1.1% | 0.4% | 5.3% | 4.7% | 1.6% | | GCE A/AS/A2 level | 67.3% | 2.7% | 0.9% | 1.8% | 5.3% | 5.3% | 4.4% | 1.8% | 2.7% | 1.8% | 4.4% | 1.8% | 0.0% | | Other quals. at L3 | 72.0% | 4.9% | 1.3% | 1.5% | 5.0% | 1.7% | 4.2% | 2.7% | 0.6% | 0.4% | 2.9% | 1.5% | 1.4% | | Level 4 quals | 69.8% | 6.5% | 1.3% | 2.4% | 3.4% | 1.3% | 4.7% | 2.2% | 0.0% | 0.9% | 3.4% | 3.4% | 0.6% | | Total | 62.5% | 7.1% | 1.2% | 2.6% | 4.0% | 2.9% | 7.4% | 3.3% | 1.6% | 0.4% | 3.1% | 2.8% | 1.0% | | Sample | 65.5% | 4.5% | 1.4% | 3.0% | 4.2% | 2.2% | 7.6% | 3.2% | 1.7% | 0.5% | 3.2% | 3.0% | 0.0% | |--------|-------|------|------|------|------|------|------|------|------|------|------|------|------|

*Ipsos MORI and London Economics (2012)*

### Table 57: Unemployed learner participation by aggregated qualification level by outcome (ILR 2011/12)

| Qualification Level | Completed and achieved | Did not complete (withdrawal or failed assessment) | Total | |---------------------|------------------------|--------------------------------------------------|-------| | Entry Level | 842 47.9% | 914 52.1% | 1,756 100.0% | | Level 1 | 2,652 48.0% | 2,869 52.0% | 5,521 100.0% | | Level 2 | 8,567 62.1% | 5,232 37.9% | 13,799 100.0% | | Level 3 | 242 42.4% | 329 57.6% | 571 100.0% | | Level 4 | 7 24.1% | 22 75.9% | 29 100.0% | | **Total** | **12,310 56.8%** | **9,366 52.1%** | **21,676 100.0%** | | **Sample** | **281 24.5%** | **865 75.5%** | **1,145 100.0%** |

*Ipsos MORI and London Economics (2012)*

### Table 58: Unemployed learner participation by disaggregated qualification level by outcome (ILR 2010/11)

| Qualification Level | Completed and achieved | Did not complete (withdrawal or failed assessment) | Total | |---------------------|------------------------|--------------------------------------------------|-------| | Entry Level/ Other | 421 60.8% | 272 39.2% | 693 100.0% | | SFL Entry Level | 421 39.6% | 642 60.4% | 1,063 100.0% | | SFL L1 | 1,454 41.9% | 2,019 58.1% | 3,473 100.0% | | Award L1 | 638 49.3% | 656 50.7% | 1,294 100.0% | | Certificate L1 | 329 74.4% | 113 25.6% | 442 100.0% | | Diploma L1 | 28 44.4% | 35 55.6% | 63 100.0% | | BTEC L1 | 46 78.0% | 13 22.0% | 59 100.0% | | NVQ L1 | 13 65.0% | 7 35.0% | 20 100.0% | | Other L1 | 144 84.7% | 26 15.3% | 170 100.0% | | SFL L2 | 4,250 61.8% | 2,630 38.2% | 6,880 100.0% | | Award L2 | 25 89.3% | 3 10.7% | 28 100.0% | | Certificate L2 | 3,617 61.1% | 2,299 38.9% | 5,916 100.0% | | Diploma L2 | 111 50.9% | 107 49.1% | 218 100.0% | | BTEC L2 | 0 0.0% | 5 100.0% | 5 100.0% | | NVQ L2 | 449 83.5% | 89 16.5% | 538 100.0% | | GCSEs | 1 10.0% | 9 90.0% | 10 100.0% | | Other quals. at L2 | 114 55.9% | 90 44.1% | 204 100.0% | | Award L3 | 14 87.5% | 2 12.5% | 16 100.0% | | Certificate L3 | 46 46.5% | 53 53.5% | 99 100.0% | | Diploma L3 | 38 20.5% | 147 79.5% | 185 100.0% | | BTEC L 3 | 4 6.3% | 59 93.7% | 63 100.0% | | NVQ L 3 | 111 84.1% | 21 15.9% | 132 100.0% | | GCE A/AS/A2 level | 0 0.0% | 2 100.0% | 2 100.0% | | Other quals. at L3 | 29 39.2% | 45 60.8% | 74 100.0% | | Level 4 quals | 7 24.1% | 22 75.9% | 29 100.0% | | **Total** | **12,310 56.8%** | **9,366 43.2%** | **21,676 100.0%** | | **Sample** | **281 24.5%** | **865 75.5%** | **1,145 100.0%** |

*London Economics (2012)*

### Table 59: Unemployed learner participation by aggregated qualification level by age (ILR 2010/11)

| | 19-24 | 25-39 | 40+ | Total | |----------|-------|-------|------|-------| | Entry Level | 1,366 | 1499 | 1381 | 4246 | | Level 1 | 2,155 | 3462 | 3331 | 8948 | | Level 2 | 5,255 | 9899 | 8651 | 23805 | | Level 3 | 4,320 | 1862 | 916 | 7098 | | Level 4 | 74 | 200 | 190 | 464 | | Total | 13,170| 16,922| 14,469| 44,561| | Sample | 579 | 742 | 634 | 1,955 |

*London Economics (2012)*

### Table 60: Unemployed learner participation by aggregated qualification level by age (ILR 2011/12)

| | 19-24 | 25-39 | 40+ | Total | |----------|-------|-------|------|-------| | Entry Level/ Other | 1,075 | 816 | 800 | 2691 | | SFL Entry Level | 291 | 683 | 581 | 1555 | | SFL L1 | 1,103 | 2126 | 1515 | 4744 | | Award L1 | 422 | 682 | 1188 | 2292 | | Certificate L1 | 341 | 275 | 326 | 942 | | Diploma L1 | 59 | 85 | 49 | 193 | | BTEC L1 | 34 | 56 | 47 | 137 | | NVQ L1 | 23 | 23 | 17 | 63 | | Other L1 | 173 | 215 | 189 | 577 | | SFL L2 | 1,997 | 4005 | 3129 | 9131 | | Award L2 | 221 | 18 | 15 | 254 | | Certificate L2 | 1,381 | 3776 | 4414 | 9571 | | Diploma L2 | 359 | 573 | 352 | 1284 | | BTEC L2 | 35 | 26 | 12 | 73 | | NVQ L2 | 396 | 688 | 368 | 1452 | | GCSEs | 343 | 72 | 25 | 440 | | Other quals. at L2 | 523 | 741 | 336 | 1600 | | Award L3 | 64 | 22 | 24 | 110 | | Certificate L3 | 129 | 228 | 194 | 551 | | Diploma L3 | 2,037 | 880 | 381 | 3298 | | BTEC L 3 | 1,365 | 211 | 44 | 1620 | | NVQ L 3 | 104 | 225 | 121 | 450 | | GCE A/AS/A2 level | 106 | 2 | 5 | 113 | | Other quals. at L3 | 515 | 294 | 147 | 956 | | Level 4 quals | 74 | 200 | 190 | 464 | | Total | 13,170| 16,922| 14,469| 44,561| | Sample | 579 | 742 | 634 | 1,955 |

*London Economics (2012)*